coding-interview-university/translations/README-ptbr.md

# Universidade de Entrevista de Programação

> I originally created this as a short to-do list of study topics for becoming a software engineer, 
> but it grew to the large list you see today. After going through this study plan, [I got hired 
> as a Software Development Engineer at Amazon](https://startupnextdoor.com/ive-been-acquired-by-amazon/?src=ciu)! 
> You probably won't have to study as much as I did. Anyway, everything you need is here.
>
> The items listed here will prepare you well for in an interview at just about any software company, 
> including the giants: Amazon, Facebook, Google or Microsoft.
>
> *Best of luck to you!*

Original: [Inglês](https://github.com/jwasham/coding-interview-university/blob/master/README.md)
    
## O que é isso?

Esse é o meu plano de estudo mensal para ir de desenvolvedor web (autodidata, sem formação em Ciência da Computação) à engenheiro de software para uma grande empresa.

![Programando no quadro branco - do Vale do Silício da HBO](https://dng5l3qzreal6.cloudfront.net/2016/Aug/coding_board_small-1470866369118.jpg)

Essa longa lista foi extraída e expandida a partir das **anotações de treinamento da Google**, então essas são as coisas que você precisa saber.
Eu adicionei alguns itens extras no final que podem aparecer na entrevista ou serem úteis para resolver um problema. Muitos itens são da obra “[Get that job at Google](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html)” (Consiga aquele trabalho na Google) de Steve Yegge’s e às vezes são expressados palavra-por-palavra nas anotações de treinamento da Google.

Isso é direcionado à **engenheiros de software novos** ou àqueles que estão migrando de desenvolvimento de software/web para engenharia de software (onde conhecimento de ciência da computação é necessário). Se você tem vários anos de experiência e está alegando muitos anos de experiência com engenharia de software, pode esperar por uma entrevista mais difícil.

Se você tem vários anos de experiência com desenvolvimento de software/web, observe que grandes empresas como Google, Amazon, Facebook e Microsoft consideram engenharia de software como algo distinto de desenvolvimento de software/web e elas requerem conhecimento de ciência da computação.

Se você quer ser um engenheiro de confiabilidade ou engenheiro de sistemas, estude mais da lista opcional (rede, segurança).

---

## Table of Contents

- [O que é isso?](#o-que-é-isso)
- [Por que usar?](#por-que-usar)
- [Como usar?](#como-usar)
- [Não ache que você não é inteligente o suficiente](#não-ache-que-você-não-é-inteligente-o-suficiente)
- [Sobre os recursos em vídeo](#sobre-os-recursos-em-vídeo)
- [Processo de Entrevista e Preparação Geral para a Entrevista](#processo-de-entrevista-e-preparação-geral-para-a-entrevista)
- [Escolha Uma Linguagem para a Entrevista](#escolha-uma-linguagem-para-a-entrevista)
- [Lista de Livros](#lista-de-livros)
- [Antes de começar](#antes-de-começar)
- [O que você não verá](#o-que-você-não-verá)
- [The Daily Plan](#the-daily-plan)
- [Conhecimento Prévio](#conhecimento-prévio)
- [Complexidade Algorítmica / Big-O / Análise assintótica](#complexidade-algorítmica--big-o--análise-assintótica)
- [Estrutura de Dados](#estrutura-de-dados)
    - [Arrays](#arrays)
    - [Linked Lists](#linked-lists)
    - [Stack](#stack)
    - [Queue](#queue)
    - [Hash table](#hash-table)
- [Mais Conhecimento](#mais-conhecimento)
    - [Binary search](#binary-search)
    - [Bitwise operations](#bitwise-operations)
- [Árvores](#árvores)
    - [Árvores - Anotações e Fundamentos](#árvores---anotações-e-fundamentos)
    - [Árvores binárias de busca: ABB](#árvores-binárias-de-busca-abb)
    - [Memória Dinâmica (heap) / Filas Prioritárias / Memória Dinâmica Binária (heap binary)](#memória-dinâmica-heap--filas-prioritárias--memória-dinâmica-binária-heap-binary)
    - árvores de busca balanceadas (conceito geral, não detalhes)
    - transversais: pré-ordem, em-ordem (ordem simétrica), pós-ordem, busca em largura, busca em profundidade
- [Sorting](#sorting)
    - selection
    - insertion
    - heapsort
    - quicksort
    - merge sort
- [Graphs](#graphs)
    - directed
    - undirected
    - adjacency matrix
    - adjacency list
    - traversals: BFS, DFS
- [Even More Knowledge](#even-more-knowledge)
    - [Recursion](#recursion)
    - [Dynamic Programming](#dynamic-programming)
    - [Object-Oriented Programming](#object-oriented-programming)
    - [Design Patterns](#design-patterns)
    - [Combinatorics (n choose k) & Probability](#combinatorics-n-choose-k--probability)
    - [NP, NP-Complete and Approximation Algorithms](#np-np-complete-and-approximation-algorithms)
    - [Caches](#caches)
    - [Processes and Threads](#processes-and-threads)
    - [Papers](#papers)
    - [Testing](#testing)
    - [Scheduling](#scheduling)
    - [Implement system routines](#implement-system-routines)
    - [String searching & manipulations](#string-searching--manipulations)
    - [Tries](#tries)
    - [Floating Point Numbers](#floating-point-numbers)
    - [Unicode](#unicode)
    - [Endianness](#endianness)
- [Networking](#networking)
- [System Design, Scalability, Data Handling](#system-design-scalability-data-handling) (if you have 4+ years experience)
- [Final Review](#final-review)
- [Coding Question Practice](#coding-question-practice)
- [Coding exercises/challenges](#coding-exerciseschallenges)
- [Once you're closer to the interview](#once-youre-closer-to-the-interview)
- [Your Resume](#your-resume)
- [Be thinking of for when the interview comes](#be-thinking-of-for-when-the-interview-comes)
- [Have questions for the interviewer](#have-questions-for-the-interviewer)
- [Once You've Got The Job](#once-youve-got-the-job)

---------------- Tudo abaixo é opcional ----------------

- [Additional Books](#additional-books)
- [Additional Learning](#additional-learning)
    - [Compilers](#compilers)
    - [Emacs and vi(m)](#emacs-and-vim)
    - [Unix command line tools](#unix-command-line-tools)
    - [Information theory](#information-theory)
    - [Parity & Hamming Code](#parity--hamming-code)
    - [Entropy](#entropy)
    - [Cryptography](#cryptography)
    - [Compression](#compression)
    - [Computer Security](#computer-security)
    - [Garbage collection](#garbage-collection)
    - [Parallel Programming](#parallel-programming)
    - [Messaging, Serialization, and Queueing Systems](#messaging-serialization-and-queueing-systems)
    - [A*](#a)
    - [Fast Fourier Transform](#fast-fourier-transform)
    - [Bloom Filter](#bloom-filter)
    - [HyperLogLog](#hyperloglog)
    - [Locality-Sensitive Hashing](#locality-sensitive-hashing)
    - [van Emde Boas Trees](#van-emde-boas-trees)
    - [Augmented Data Structures](#augmented-data-structures)
    - [N-ary (K-ary, M-ary) trees](#n-ary-k-ary-m-ary-trees)
    - [Balanced search trees](#balanced-search-trees)
        - AVL trees
        - Splay trees
        - Red/black trees
        - 2-3 search trees
        - 2-3-4 Trees (aka 2-4 trees)
        - N-ary (K-ary, M-ary) trees
        - B-Trees
    - [k-D Trees](#k-d-trees)
    - [Skip lists](#skip-lists)
    - [Network Flows](#network-flows)
    - [Disjoint Sets & Union Find](#disjoint-sets--union-find)
    - [Math for Fast Processing](#math-for-fast-processing)
    - [Treap](#treap)
    - [Linear Programming](#linear-programming)
    - [Geometry, Convex hull](#geometry-convex-hull)
    - [Discrete math](#discrete-math)
    - [Machine Learning](#machine-learning)
- [Additional Detail on Some Subjects](#additional-detail-on-some-subjects)
- [Video Series](#video-series)
- [Computer Science Courses](#computer-science-courses)

---

## Por que usar?

Quando eu comecei esse projeto, eu não sabia diferenciar memória dinâmica de memória estática, não sabia notação Big-O, árvores, ou como percorrer um gráfico. Se eu tivesse que escrever um algoritmo de ordenação, eu posso te dizer que ele não seria muito bom.
Todas as estruturas de dados que eu já usei eram construídas dentro da linguagem, e eu não sabia como elas funcionavam por debaixo dos panos. Eu nunca tive que gerenciar memória a não ser que um processo que eu estava rodando desse um erro de "memória insuficiente", nesse caso eu teria que dar um jeito. Eu já usei alguns arrays multidimensionais na minha vida e milhares de arrays associativos, mas eu nunca criei estruturas de dados do zero.

É um longo plano. Você vai levar meses. Se você já é familiarizado com muitas dessas coisas, você vai precisar de muito menos tempo. 

## Como usar

Tudo abaixo é um esboço, e você deve abordar os itens em ordem de cima para baixo.

Eu estou usando a sintaxe de markdown especial do Github, incluindo listas de tarefas para verificar o progresso.

**Crie um novo branch para você verificar itens assim, apenas coloque um x entre os colchetes: [x]**


    Bifurque (fork) um branch e siga os comandos abaixo

`git checkout -b progress`

`git remote add jwasham https://github.com/jwasham/coding-interview-university`

`git fetch --all`

    Marque todas as caixas com X depois que você completar suas alterações

`git add . `

`git commit -m "Marked x" `

`git rebase jwasham/master `

`git push --force `

[Mais sobre a sintaxe de markdown especial do Github](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown)

## Não ache que você não é inteligente o suficiente
- Engenheiros de software bem sucedidos são inteligentes, mas muitos são inseguros quanto à própria inteligência.
- [O mito do Programador Gênio](https://www.youtube.com/watch?v=0SARbwvhupQ)
- [É perigoso ir sozinho: Batalhando os monstros invisíveis na indústria de Tecnologia](https://www.youtube.com/watch?v=1i8ylq4j_EY)

## Sobre os recursos em vídeo

Alguns vídeos estão disponíveis somente ao ingressar em um curso no Coursera, EdX, ou Lynda.com. Esses são chamados de MOOCs (Curso Online Aberto e Massivo).
Às vezes as aulas não estão em sessão, nesse caso você terá que esperar alguns meses, portanto não terá acesso até lá. Os cursos da Lynda.com não são gratuitos.

    Eu agradeceria a ajuda de vocês em adicionar fontes públicas gratuitas e sempre disponíveis, como vídeos do YouTube para acompanhar os vídeos de curso online.
    Eu gosto de usar palestras de universidades;


## Processo de Entrevista e Preparação Geral para a Entrevista

- [ ] [ABC: Always Be Coding](https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4)
- [ ] [Whiteboarding](https://medium.com/@dpup/whiteboarding-4df873dbba2e#.hf6jn45g1)
- [ ] [Effective Whiteboarding during Programming Interviews](http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/)
- [ ] [Demystifying Tech Recruiting](https://www.youtube.com/watch?v=N233T0epWTs)
- [ ] Cracking The Coding Interview Set 1:
    - [ ] [Gayle L McDowell - Cracking The Coding Interview (video)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ)
    - [ ] [Cracking the Coding Interview with Author Gayle Laakmann McDowell (video)](https://www.youtube.com/watch?v=aClxtDcdpsQ)
- [ ] How to Get a Job at the Big 4:
    - [ ] [How to Get a Job at the Big 4 - Amazon, Facebook, Google & Microsoft (video)](https://www.youtube.com/watch?v=YJZCUhxNCv8)

- [ ] Prep Courses:
    - [ ] [Software Engineer Interview Unleashed (paid course)](https://www.udemy.com/software-engineer-interview-unleashed):
        - Learn how to make yourself ready for software engineer interviews from a former Google interviewer.
    - [ ] [Python for Data Structures, Algorithms, and Interviews! (paid course)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/): 
        - A Python centric interview prep course which covers data structures, algorithms, mock interviews and much more.

## Escolha Uma Linguagem para a Entrevista

Você pode escolher uma linguagem com a qual você esteja confortável para fazer a parte de programação (parte prática) da entrevista, mas para grandes empresas, essas são ótimas opções:

- C++
- Java
- Python

Você também poderia usar essas, mas dê uma lida por aí antes. Podem haver avisos:

- JavaScript
- Ruby

Você precisa estar confortável com a linguagem e ser bem informado.

Leia mais sobre as escolhas:
- http://www.byte-by-byte.com/choose-the-right-language-for-your-coding-interview/
- http://blog.codingforinterviews.com/best-programming-language-jobs/

[Veja recursos de linguagens aqui](programming-language-resources.md)

Você vai ver aprendizado de C, C++ e Python incluído abaixo, porque é o que estou aprendendo. Tem alguns livros envolvidos, veja no final.

## Lista de Livros

Essa é uma lista menor comparada à que eu usei. Está abreviado para economizar seu tempo.

### Preparação para a Entrevista

- [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html) (Entrevistas de Programação Expostas: Segredos para Conseguir Seu Próximo Emprego, 2ª Edição)
    - respostas em C++ e Java
    - esse é um bom aquecimento para o Cracking the Coding Interview (Decifrando a Entrevista de Programação)
    - não é muito difícil, a maioria dos problemas poderão ser mais fáceis que aqueles que você verá em uma entrevista (de acordo com o que li)
- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/) (Decifrando a Entrevista de Programação).
    - respostas em Java

Se você tem muito tempo sobrando:

- [ ] [Elements of Programming Interviews (C++ version)](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836) (Elementos de Entrevistas de Programação (Versão C++))
- [ ] [Elements of Programming Interviews (Java version)](https://www.amazon.com/Elements-Programming-Interviews-Java-Insiders/dp/1517435803/) (Elementos de Entrevistas de Programação (Versão Java))

### Arquitetura de Computador

Se estiver com pouco tempo:

- [ ] [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038) (Escreva um Excelente Código: Volume 1: Compreendendo a Máquina)
    - O livro foi publicado em 2004, e está meio vencido, mas é um recurso maravilhoso para compreender um computador resumidamente.
    - O autor inventou HLA (High-level Assembly ou, no português, Assembly de alto nível), então considere as menções e exemplos em HLA com cautela. Não é usado amplamente, mas contém exemplos decentes de como o assembly funciona.
    - Esses capítulos valem a pena serem lidos para lhe dar uma boa base:
        - Chapter 2 - Numeric Representation (Capítulo 2 - Representação Numérica)
        - Chapter 3 - Binary Arithmetic and Bit Operations
        - Chapter 4 - Floating-Point Representation
        - Chapter 5 - Character Representation
        - Chapter 6 - Memory Organization and Access
        - Chapter 7 - Composite Data Types and Memory Objects
        - Chapter 9 - CPU Architecture
        - Chapter 10 - Instruction Set Architecture
        - Chapter 11 - Memory Architecture and Organization 

Se você tem mais tempo (eu quero esse livro):

- [ ] [Computer Architecture, Fifth Edition: A Quantitative Approach](https://www.amazon.com/dp/012383872X/) (Arquitetura de Computador, Quinta Edição: Uma Abordagem Quantitativa)
    - Se quiser uma versão mais rica e atualizada (2011), mas com um tratamento mais longo

### Específico de Linguagem

**Você precisa escolher uma linguagem para a entrevista (veja acima).** Aqui estão minhas recomendações por linguagem. Eu não tenho recursos para todas as linguagens. Contribuições são bem-vindas.

Se você ler um desses, você deverá ter todo conhecimento de estrutura de dados e algoritmos que precisará para começar a resolver problemas de programação. 
**Você pode pular todas as aulas em vídeo nesse projeto**, a não ser que você queira uma revisão.

[Recursos adicionais específicos a cada linguagem aqui.](programming-language-resources.md)

### C++

Eu ainda não li esses dois, mas eles são muito bem avaliados e escritos por Sedgewick. Ele é ótimo.

- [ ] [Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/) (Algoritmos em C++, Partes 1-4: Fundamentos, Estrutura de Dados, Ordenação, Busca).
- [ ] [Algorithms in C++ Part 5: Graph Algorithms](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/) (Algoritmos em C++ Parte 5: Algoritmos de Gráfico)

Se você tiver uma recomendação melhor para C++, por favor me informe. Busco por recursos completos. 

### Java

- [ ] [Algorithms (Sedgewick and Wayne)](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X/) (Algoritmos (Sedgewick e Wayne))
    - vídeos com conteúdo do livro (e Sedgewick!):
        - [Algorithms I](https://www.youtube.com/user/algorithmscourses/playlists?view=50&sort=dd&shelf_id=2) (Algoritmos I)
        - [Algorithms II](https://www.youtube.com/user/algorithmscourses/playlists?shelf_id=3&view=50&sort=dd) (Algoritmos II)

OU:

- [ ] [Data Structures and Algorithms in Java](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/) (Estrutura de Dados e Algoritmos em Java)
    - por Goodrich, Tamassia, Goldwasser
    - usado como texo opcional para o curso introdutório de Ciência da Computação na Universidade da Califórnia em Berkeley
    - veja o meu resumo sobre a versão em Python abaixo. Esse livro abrange os mesmos tópicos.

### Python

- [ ] [Data Structures and Algorithms in Python](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/) (Estrutura de Dados e Algoritmos em Python)
    - por Goodrich, Tamassia, Goldwasser
    - Eu adorei esse livro. Ele cobriu tudo e mais.
    - Código pythonico.
    - meu brilhante resumo: https://startupnextdoor.com/book-report-data-structures-and-algorithms-in-python/


### Livros Opcionais

**Algumas pessoas recomendam esses, mas eu acho que está além do necessário, a não ser que você tenha muitos anos de experiência em engenharia de software e está esperando por uma entrevista muito mais difícil:**

- [ ] [Algorithm Design Manual](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202) (Skiena) (Manual de Design de Algoritmo)
    - Como uma revisão e reconhecimento de problema
    - A parte de catálogos de algoritmos está muito além da margem de dificuldade que você terá numa entrevista.
    - Esse livro tem 2 partes:
        - livro de aula sobre estrutura de dados e algoritmos
            - prós:
                - é uma boa revisão assim como qualquer texto de algoritmos seria
                - boas estórias da experiência dele resolvendo problemas na indústria e na universidade
                - exemplo de código em C
            - contras:
                - pode ser tão denso ou impenetrável quanto CLRS (Introdução a Algoritmos), e em alguns casos, CLRS pode ser uma alternativa melhor para alguns temas
                - capítulos 7, 8 e 9 podem ser sofridos para acompanhar, já que alguns itens não são bem explicados ou requerem mais cérebro do que eu tenho
                - não me entenda mal: Eu gosto de Skiena, do estilo de ensino dele, e maneirismos, mas pode não ser um material do tipo da universidade Stony Brook.
        - catálogo de algoritmos
            - essa é a verdadeira razão para você comprar esse livro.
            - prestes a chegar nessa parte. Vou atualizar aqui assim que eu terminar de ler essa parte.
    - Pode alugar no kindle
    - Half.com é um ótimo recurso para livros com bons preços.
    - Respostas:
        - [Solutions](http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)) (Soluções)
        - [Solutions](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/) (Soluções)
    - [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata)

- [ ] [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844) (Introdução à Algoritmos)
    - **Importante:** Ler esse livro só terá um valor limitado. Esse livro é ótimo para revisão de algoritmos e estrutura de dados, mas não irá te ensinar a escrever um bom código. Você deve ser capaz de programar uma solução decente eficientemente.
    - Half.com é um ótimo recurso para livros com bons preços.
    - também conhecido como CLR, às vezes CLRS, porque Stein estava atrasado para o negócio

- [ ] [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880) (Pérolas de Programação)
    - Os primeiros capítulos apresentam solução inteligentes para problemas de programação (alguns bem velhos usando suporte magnético) mas
      isso é só uma introdução. Esse é um guia sobre design e arquitetura de programa, parecido com Code Complete, mas muito mais curto.

- ~~"Algorithms and Programming: Problems and Solutions" by Shen ("Algoritmos e Programação: Problemas e Soluções" por Shen)~~
    - Um bom livro, mas depois de trabalhar nos problemas em várias páginas eu fiquei frustrado com o Pascal, loops do...while, arrays de 1 índice (index), e resultados de satisfação pós-condição pouco claros.  
    - Prefiro gastar tempo em problemas de programação de outro livro oi problemas de programação online.


## Antes de começar

Essa lista cresceu por longos meses, e sim, ela meio que saiu do controle.

Aqui estão alguns erros que eu cometi para que você tenha uma experiência melhor.

### 1. Você não se lembrará disso tudo

Assisti a horas de vídeos e fiz anotações e meses depois havia muito que eu não me lembrava. Eu passei 3 dias revisando minhas anotaçes e fazendo flashcards para que eu pudesse relembrar.

Por favor, leia para que você não cometa os meus erros:

[Retaining Computer Science Knowledge](https://startupnextdoor.com/retaining-computer-science-knowledge/)

### 2. Use Flashcards

Para solucionar o problema, eu fiz um pequeno site de flashcards onde eu poderia adicionar dois tipos de flashcards: genérico e código.  
Cada cartão tem formatação diferente.

Eu fiz um website focado em mobile para que eu pudesse rever no meu celular, tablet, onde quer que eu esteja.

Faça o seu próprio, grátis:

- [Repositório de flashcards](https://github.com/jwasham/computer-science-flash-cards)
- [Minha base de dados de flashcards (antigo - 1200 cartões)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham.db): 
- [Minha base de dados de flashcards (novo - 1800 cartões)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham-extreme.db):

Tenha em mente que eu exagerei e tenho cartas abrangendo desde linguagem assembly e trivialidades de Python até aprendizado de máquina e estatísticas. É demais para o que é requerido. 

**Nota:** A primeira vez que você reconhece que sabe a resposta, não a marque como conhecida. Você tem que ver o mesmo cartão e respondê-lo várias vezes corretamente antes de realmente conhecê-lo. A repetição colocará esse conhecimento mais aprodundado em seu cérebro.

Uma alternativa ao uso do meu site de flashcards é [Anki](http://ankisrs.net/), que me foi recomendado várias vezes. Ele usa um sistema de repetição para ajuda-lo a se lembrar.
É fácil de usar, está disponível em todas as plataformas e possui um sistema de sincronização em nuvem. Ele custa 25 dólares no iOS, mas é gratuito em outras plataformas.

Meu banco de dados de flashcards em formato Anki: https://ankiweb.net/shared/info/25173560 (obrigado [@xiewenya](https://github.com/xiewenya))

### 3. Reveja, Reveja e Reveja

Eu mantenho um conjunto de anotações em ASCII, OSI stack, Notações Big-O, e muito mais. Eu os estudo quando tenho algum tempo livre.

Faça uma pausa durante os problemas de programação por meia hora e passe por seus flashcards.

### 4. Foco

Há um monte de distrações que podem ocupar um tempo valioso. Foco e concentração são difíceis.

## O que você não verá 

Essas são tecnologias predominantes, mas não são partes desse plano de estudo:

- SQL
- Javascript
- HTML, CSS, e outras tecnologias de front-end

## The Daily Plan

Some subjects take one day, and some will take multiple days. Some are just learning with nothing to implement.

Each day I take one subject from the list below, watch videos about that subject, and write an implementation in:
- C - using structs and functions that take a struct * and something else as args.
- C++ - without using built-in types
- C++ - using built-in types, like STL's std::list for a linked list
- Python - using built-in types (to keep practicing Python)
- and write tests to ensure I'm doing it right, sometimes just using simple assert() statements
- You may do Java or something else, this is just my thing.

You don't need all these. You need only [one language for the interview](#pick-one-language-for-the-interview).

Why code in all of these?
- Practice, practice, practice, until I'm sick of it, and can do it with no problem (some have many edge cases and bookkeeping details to remember)
- Work within the raw constraints (allocating/freeing memory without help of garbage collection (except Python))
- Make use of built-in types so I have experience using the built-in tools for real-world use (not going to write my own linked list implementation in production)

I may not have time to do all of these for every subject, but I'll try.

You can see my code here:
 - [C] (https://github.com/jwasham/practice-c)
 - [C++] (https://github.com/jwasham/practice-cpp)
 - [Python] (https://github.com/jwasham/practice-python)

You don't need to memorize the guts of every algorithm.

Write code on a whiteboard or paper, not a computer. Test with some sample inputs. Then test it out on a computer.

## Conhecimento Prévio

- [ ] **Aprenda C**
    - C está em todo lugar. Você vai ver exemplos em livros, aulas, vídeos, em todo lugar enquanto você estiver estudando.
    - [ ] [C Programming Language, Vol 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628) (Linguagem de Programação C, Vol 2)
        - Esse é um livro curto, mas vai te ajudar a ter um ótimo domínio da linguagem C e se você praticar um pouco 
            você irá se tornar proficiente rapidamente. Entender C te ajuda a entender como os programas e a memória funcionam.
        - [answers to questions](https://github.com/lekkas/c-algorithms) (respostas para as questões) 

- [ ] **Como computadores processam um programa:**
    - [ ] [How does CPU execute program (video)](https://www.youtube.com/watch?v=42KTvGYQYnA) (Como uma CPU executa um programa - vídeo)
    - [ ] [Machine Code Instructions (video)](https://www.youtube.com/watch?v=Mv2XQgpbTNE) (Instruções de Código de Máquina - vídeo)

## Complexidade Algorítmica / Big-O / Análise assintótica
- nada para implementar
- [ ] [Harvard CS50 - Asymptotic Notation (video)](https://www.youtube.com/watch?v=iOq5kSKqeR4) (Harvard CS50 - Notação Assintótica - vídeo)
- [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU) (Notações Big-O (rápido tutorial geral) - vídeo)
- [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN) (Notação Big-O (e Omega e Theta) - melhor explicação matemática - vídeo)
- [ ] Skiena:
    - [video](https://www.youtube.com/watch?v=gSyDMtdPNpU&index=2&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [slides](http://www3.cs.stonybrook.edu/~algorith/video-lectures/2007/lecture2.pdf)
- [ ] [A Gentle Introduction to Algorithm Complexity Analysis](http://discrete.gr/complexity/) (Uma Introdução Gentil a Análise de Complexidade Algoritmica)
- [ ] [Orders of Growth (video)](https://class.coursera.org/algorithmicthink1-004/lecture/59) (Ordens de Crescimento - vídeo)
- [ ] [Asymptotics (video)](https://class.coursera.org/algorithmicthink1-004/lecture/61) (Assintóticas - vídeo)
- [ ] [UC Berkeley Big O (video)](https://youtu.be/VIS4YDpuP98) (Big-O - Universidade da Califórnia em Berkeley - vídeo)
- [ ] [UC Berkeley Big Omega (video)](https://youtu.be/ca3e7UVmeUc) (Grande Omega - Universidade da Califórnia em Berkeley - vídeo)
- [ ] [Amortized Analysis (video)](https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN) (Análise Amortizada - vídeo)
- [ ] [Illustrating "Big O" (video)](https://class.coursera.org/algorithmicthink1-004/lecture/63) (Ilustrando "Big-O" - vídeo)
- [ ] TopCoder (inclui relações de recorrência e teorema mestre):
    - [Computational Complexity: Section 1](https://www.topcoder.com/community/data-science/data-science-tutorials/computational-complexity-section-1/) (Complexidade Computacional: Seção 1)
    - [Computational Complexity: Section 2](https://www.topcoder.com/community/data-science/data-science-tutorials/computational-complexity-section-2/) (Complexidade Computacional: Seção 2)
- [ ] [Cheat sheet](http://bigocheatsheet.com/) (Folha de Consultas)


    Se alguma das aulas forem muito "matemáticas", você pode pular para o final e 
    ver o vídeo de matemática discreta para ganhar um conhecimento base.

## Estrutura de Dados

- ### Arrays
    - Implementar um vetor de redimensionamento automático.
    - [ ] Descrição:
        - [Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays)
        - [UCBerkley CS61B - Linear and Multi-Dim Arrays (video)](https://youtu.be/Wp8oiO_CZZE?t=15m32s) (Arrays lineares e multidimensionais - vídeo)
        - [Basic Arrays (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Basic-arrays/149042/177104-4.html) (Arrays básicos - vídeo)
        - [Multi-dim (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Multidimensional-arrays/149042/177105-4.html) (Multidimensionais - vídeo)
        - [Dynamic Arrays (video)](https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays) (Arrays Dinâmicos - vídeo)
        - [Jagged Arrays (video)](https://www.youtube.com/watch?v=1jtrQqYpt7g) (Arrays Multidimensionais - vídeo)
        - [Jagged Arrays (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Jagged-arrays/149042/177106-4.html) (Arrays Multidimensionais - vídeo)
        - [Resizing arrays (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Resizable-arrays/149042/177108-4.html) (Arrays Dinâmicos)
    - [ ] Implementar um vetor (array mutável com redimensionamento automático):
        - [ ] Praticar programação usando arrays e ponteiros, e matemática de ponteiros para pular para um índice ao invés de usar indexação.
        - [ ] novo array de dados brutos com memória alocada
            - pode alocar array de números inteiros por de baixo dos panos, só não pode usar seus recursos
            - começa com 16, ou se o número inicial for maior, usar potência de 2 - 16, 32, 64, 128
        - [ ] size() - número de itens
        - [ ] capacity() - número de itens que pode conter
        - [ ] is_empty()
        - [ ] at(index) - retorna o item que está no índice fornecido, dá erro se o índice estiver fora da capacidade do array
        - [ ] push(item)
        - [ ] insert(índice, item) - insere "item" no "índice", muda o valor daquele índice e move os elementos excedentes para a direita
        - [ ] prepend(item) - pode usar o insert acima no índice 0
        - [ ] pop() - remove do final, retorna o valor
        - [ ] delete(índice) - deleta o item no índice fornecido, deslocando todos os elementos excedentes para a esquerda
        - [ ] remove(item) - busca pelo valor e remove o índice contendo ele (mesmo que esteja em múltiplos lugares)
        - [ ] find(item) - busca pelo valor e retorna o primeiro índice com aquele valor, -1 se não encontrar
        - [ ] resize(nova_capacidade) // função privada
            - quando você atinge o limite da capacidade, redimensone para dobrar a capacidade
            - quando estiver usando pop() em um item, se o tamanho for 1/4 da capacidade, redimensionar para a metade da capacidade
    - [ ] Tempo
        - O(1) para adicionar/remover no final (amortizado para alocações para mais espaço), índice ou atualização
        - O(n) para inserir/remover em algum outro lugar
    - [ ] Espaço
        - contíguo na memória, então proximidade ajuda no desempenho
        - espaço necessário = (capacidade do array, a qual é >= n) * tamanho do item, mas mesmo que seja 2n, ainda será O(n)

- ### Listas Ligadas
    - [ ] Descrição:
        - [ ] [Singly Linked Lists (video)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists) (listas ligadas individualmente - vídeo)
        - [ ] [CS 61B - Linked Lists (video)](https://www.youtube.com/watch?v=sJtJOtXCW_M&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=5) (CS 61B - Listas Ligadas - vídeo)
    - [ ] [C Code (video)](https://www.youtube.com/watch?v=QN6FPiD0Gzo) (Código em C - vídeo)
            - não o vídeo inteiro, apenas as partes sobre estrutura de nodes (nós) e alocação de memória.
    - [ ] Listas Ligadas vs Arrays:
        - [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays) (Fundamental: Listas Ligadas vs Arrays - vídeo)
        - [In The Real World Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/QUaUd/in-the-real-world-lists-vs-arrays) (No Mundo Real: Listas Ligadas vs Arrays - vídeo)
    - [ ] [why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo) (por que você deve evitar listas ligadas - vídeo)
    - [ ] Peguei vocês: você precisa de conhecimento de ponteiro para ponteiro:
        (para quando você passar um ponteiro para uma funcção que poderá mudar o endereço para o qual o ponteiro aponta)
        Essa página é só para ter uma noção sobre ponteiro para ponteiro. Eu não recomendo o estilo transversal dessa lista. Legibilidade e manutenção sofrem devido à engenhosidade.
        - [Pointers to Pointers](https://www.eskimo.com/~scs/cclass/int/sx8.html) (Ponteiros para Ponteiros)
    - [ ] implementar (eu fiz com e sem ponteiro de cauda, ponteiro que aponta para o último node (nó) da lista):
        - [ ] size() - retorna o número de elementos de dados na lista
        - [ ] empty() - boleano retorna verdadeiro se estiver vazio
        - [ ] value_at(índice) - retorna o valor do item n (começando no 0 para o primeiro)
        - [ ] push_front(valor) - adiciona um item no início da lista, logo antes do seu atual primeiro elemento
        - [ ] pop_front() - remove o item do início da lista e retorna o seu valor
        - [ ] push_back(valor) - adiciona um item no final da lista
        - [ ] pop_back() - remove um item do final e retorna seu valor
        - [ ] front() - obtém valor do item que está no início da lista
        - [ ] back() - obtém valor do item que está no final da lista
        - [ ] insert(índice, valor) - insere "valor" no "índice", e então o item atual naquele índice é apontado pelo novo item no "índice"
        - [ ] erase(índice) - remove o node (nó) no índice fornecido
        - [ ] value_n_from_end(n) - retorna o valor do node (nó) na posição n a partir do final da lista
        - [ ] reverse() - reverte a lista
        - [ ] remove_value(valor) - remove o primeiro item na lista com esse valor
    - [ ] Listas Ligadas Duplamente
        - [Description (video)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists) (Descrição - vídeo)
        - Não há necessidade de implementar

- ### Stack
    - [ ] [Stacks (video)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks)
    - [ ] [Using Stacks Last-In First-Out (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-stacks-last-first-out/149042/177120-4.html) (Usando Stacks Último a Entrar Primeiro a Sair - vídeo)
    - [ ] Não implementarei. Implementar com array é trivial.

- ### Queue (Fila)
    - [ ] [Using Queues First-In First-Out(video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-queues-first-first-out/149042/177122-4.html) (Usando queues FIFO(Primeiro a entrar, último a sair) - vídeo)
    - [ ] [Queue (video)](https://www.coursera.org/learn/data-structures/lecture/EShpq/queue)
    - [ ] [Circular buffer/FIFO](https://en.wikipedia.org/wiki/Circular_buffer) (Buffer circular/Primeiro a entrar, último a sair)
    - [ ] [Priority Queues (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Priority-queues-deques/149042/177123-4.html) (Queues com Prioridade - vídeo)
    - [ ] Implementar usando lista ligada, com ponteiro de cauda (aponta para o último elemento de uma lista):
        - enqueue(valor) - adiciona "valor" na posição na cauda (final da lista)
        - dequeue() - retorna um valor e remove o elemento menos recentemente adicionado (início da lista))
        - empty()
    - [ ] Implementar usando arrays de tamanho-fixo:
        - enqueue(valor) - adiciona um item no final do armazenamento disponível
        - dequeue() - retorna um valor e remove um elemento menos recentemente adicionado 
        - empty()
        - full()
    - [ ] Custo:
        - uma implementação ruim usando lista ligada na qual você coloca na fila (enqueue) no head (cabeça/início da lista) e tira da fila (dequeue) no tail (cauda/final da lista) seria O(n)
            porque você precisaria do penúltimo elemento, causando uma transversal completa a cada dequeue 
        - enqueue: O(1) (amortizado, lista ligada e array [sondagem])
        - dequeue: O(1) (lista ligada e array)
        - empty (vazio): O(1) (lista ligada e array)

- ### Tabela hash (no português: Tabela de dispersão)
    - [ ] vídeos:
        - [ ] [Hashing with Chaining (video)](https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8) (Hashing com Encadeamento - vídeo)
        - [ ] [Table Doubling, Karp-Rabin (video)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) (Duplicação de Tabela, Karp-Rabin - vídeo)
        - [ ] [Open Addressing, Cryptographic Hashing (video)](https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) (Endereçamento Aberto, Hashing Criptográfico - vídeo)
        - [ ] [PyCon 2010: The Mighty Dictionary (video)](https://www.youtube.com/watch?v=C4Kc8xzcA68) (PyCon 2010: O Poderoso Dicionário (vídeo)
        - [ ] [(Advanced) Randomization: Universal & Perfect Hashing (video)](https://www.youtube.com/watch?v=z0lJ2k0sl1g&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=11) ((Avançado) Randomização: Hashing Perfeito & Universal - vídeo)
        - [ ] [(Advanced) Perfect hashing (video)](https://www.youtube.com/watch?v=N0COwN14gt0&list=PL2B4EEwhKD-NbwZ4ezj7gyc_3yNrojKM9&index=4) ((Avançado) Hashing perfeito - vídeo)

    - [ ] Cursos Online:
        - [ ] [Understanding Hash Functions (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Understanding-hash-functions/149042/177126-4.html) (Compreendendo Funções Hash - vídeo)
        - [ ] [Using Hash Tables (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-hash-tables/149042/177127-4.html) (Usando Tabelas Hash - vídeo)
        - [ ] [Supporting Hashing (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Supporting-hashing/149042/177128-4.html) (Hashing de Suporte - vídeo)
        - [ ] [Language Support Hash Tables (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Language-support-hash-tables/149042/177129-4.html) (Tabelas Hash de Suporte de Linguagem - vídeo)
        - [ ] [Core Hash Tables (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables) (Fundamental: Tabelas Hash - vídeo)
        - [ ] [Data Structures (video)](https://www.coursera.org/learn/data-structures/home/week/3) (Estruturas de Dados - vídeo)
        - [ ] [Phone Book Problem (video)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem) (Problema da Lista Telefônica (vídeo) )
        - [ ] tabelas hash distribuídas:
            - [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox) (Uploads Instantâneos E Otimização de Armazenamento no Dropbox - vídeo)
            - [Distributed Hash Tables (video)](https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables) (Tabelas Hash Distribuídas - vídeo)

    - [ ] implementar com array usando sondagem linear
        - hash(k, m) - m é o tamanho da tabela hash
        - add(chave, valor) - se a chave já existe, atualizar o valor
        - exists(chave)
        - get(chave)
        - remove(chave)

## Mais Conhecimento

- ### Busca binária
    - [ ] [Binary Search (video)](https://www.youtube.com/watch?v=D5SrAga1pno) (Busca Binária - vídeo)
    - [ ] [Binary Search (video)](https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search) (Busca Binária - vídeo)
    - [ ] [detail](https://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/) (detalhes)
    - [ ] Implementar:
        - busca binária (em um array ordenado de números inteiros)
        - busca binária usando recursividade

- ### Lógica binária 
    - [ ] [Bits cheat sheet](https://github.com/jwasham/google-interview-university/blob/master/extras/cheat%20sheets/bits-cheat-cheet.pdf) (Folha de consultas sobre Bits) - você deve conhecer várias das potências de 2 de (2^1 até 2^16 e 2^32)
    - [ ] Consiga um bom entendimento sobre manipulação de bits com: &, |, ^, ~, >>, <<
        - [ ] [words](https://en.wikipedia.org/wiki/Word_(computer_architecture)) (palavras)
        - [ ] Boa introdução:
            [Bit Manipulation (video)](https://www.youtube.com/watch?v=7jkIUgLC29I) (Manipulação de Bit - vídeo)
        - [ ] [C Programming Tutorial 2-10: Bitwise Operators (video)](https://www.youtube.com/watch?v=d0AwjSpNXR0) (Tutorial de Programação em C 2-10: Operadores Binários - vídeo)
        - [ ] [Bit Manipulation](https://en.wikipedia.org/wiki/Bit_manipulation) (Manipulação de Bit)
        - [ ] [Bitwise Operation](https://en.wikipedia.org/wiki/Bitwise_operation) (Lógica Binária)
        - [ ] [Bithacks](https://graphics.stanford.edu/~seander/bithacks.html) (Snippets/Fragmentos de código, um tipo de cheatsheet (folha de consultas))
        - [ ] [The Bit Twiddler](http://bits.stephan-brumme.com/)
        - [ ] [The Bit Twiddler Interactive](http://bits.stephan-brumme.com/interactive.html) (Interativo)
    - [ ] Complemento de 2 e 1
        - [Binary: Plusses & Minuses (Why We Use Two's Complement) (video)](https://www.youtube.com/watch?v=lKTsv6iVxV4) (Binário: Vantagens & Desvantagens (Por Que Usamos Complemento de 2) - vídeo)
        - [1s Complement](https://en.wikipedia.org/wiki/Ones%27_complement) (Complemento de 1)
        - [2s Complement](https://en.wikipedia.org/wiki/Two%27s_complement) (Complemento de 2)
    - [ ] contagem de bits fixos
        - [4 ways to count bits in a byte (video)](https://youtu.be/Hzuzo9NJrlc) (4 maneiras de contar bits em um byte - vídeo)
        - [Count Bits](https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan) (Contagem de Bits)
        - [How To Count The Number Of Set Bits In a 32 Bit Integer](http://stackoverflow.com/questions/109023/how-to-count-the-number-of-set-bits-in-a-32-bit-integer) (Como Contar O Número De Bits Fixos Em um Número inteiro de 32 bits)
    - [ ] arredondar para a próxima potência de 2:
        - [Round Up To Next Power Of Two](http://bits.stephan-brumme.com/roundUpToNextPowerOfTwo.html) (Arredondar Para Cima Para A Próxima Potência De Dois)
    - [ ] trocar valores:
        - [Swap](http://bits.stephan-brumme.com/swap.html) (Trocar)
    - [ ] valor absoluto:
        - [Absolute Integer](http://bits.stephan-brumme.com/absInteger.html) (Número Inteiro Absoluto)

## Árvores

- ### Árvores - Anotações e Fundamentos
    - [ ] [Series: Core Trees (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees) (Série: Árvores Fundamentais - vídeo)
    - [ ] [Series: Trees (video)](https://www.coursera.org/learn/data-structures/lecture/95qda/trees) (Série: Árvores - vídeo)
    - contrução básica de árvore
    - transversal
    - algorítmos de manipulação
    - Busca em largura (conhecido no Inglês como BFS ou breadth-first search)
        - [MIT (vídeo)](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13)
        - ordem de nível (busca em largura, usando filas)
            complexidade de tempo: O(n)
            complexidade de espaço: melhor: O(1), pior: O(n/2)=O(n)
    - Busca em profundidade (conhecido no Inglês como DFS ou depth-first search)
        - [MIT (vídeo)](https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14)
        - anotações:
            complexidade de tempo: O(n)
            space complexity:
                melhor: O(log n) - altura média da árvore
                pior: O(n)
        - em-ordem ou ordem simétrica(na busca em profundidade (ou DFS): percorre subárvore esquerda em ordem simétrica (em-ordem), visita a raiz, percorre subárvore direita em ordem simétrica)
        - pós-ordem (na busca em profundidade (ou DFS): percorre subárvore esquerda em pós-ordem, percorre subárvore direita em pós-ordem, visita a raiz)
        - pré-ordem (na busca em profundidade (ou DFS): visita a raiz, percorre subárvore esquerda em pré-ordem, percorre subárvore direita em pré-ordem)

- ### Árvores binárias de busca: ABB
    - [ ] [Binary Search Tree Review (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6) (Revisão de Árvores Binárias de Busca - vídeo)
    - [ ] [Série (vídeo)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees)
        - começa com tabela de símbolos e passa por aplicações de ABB
    - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction) (Introdução - vídeo)
    - [ ] [MIT (vídeo)](https://www.youtube.com/watch?v=9Jry5-82I68)
    - C/C++:
        - [ ] [Binary search tree - Implementation in C/C++ (video)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28) (Árvore binária de busca - Implementação em C/C++ - vídeo)
        - [ ] [BST implementation - memory allocation in stack and heap (video)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29) (Implementação de ABB - alocação de memória estática (stack) e dinâmica (heap) - vídeo)
        - [ ] [Find min and max element in a binary search tree (video)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) (Encontrar elementos min e max em uma árvore binária de busca - vídeo)
        - [ ] [Find height of a binary tree (video)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31) (Encontrar altura de uma árvore binária - vídeo)
        - [ ] [Binary tree traversal - breadth-first and depth-first strategies (video)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32) (Percurso de uma árvore binária - estratégias de busca em largura e busca em profundidade - vídeo)
        - [ ] [Binary tree: Level Order Traversal (video)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) (Árvore binária: Percurso de Ordens de Níveis - vídeo)
        - [ ] [Binary tree traversal: Preorder, Inorder, Postorder (video)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) (Percurso de árvore binária: Pré-ordem, Em-ordem (ordem simétrica), Pós-ordem - vídeo)
        - [ ] [Check if a binary tree is binary search tree or not (video)](https://www.youtube.com/watch?v=yEwSGhSsT0U&index=35&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) (Verificar se uma árvore binária é uma árvore binária de busca ou não - vídeo)
        - [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36) (Deletar um nó de uma Árvore Binária de Busca - vídeo)
        - [ ] [Inorder Successor in a binary search tree (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P) (Sucessor Em-ordem em uma árvore binária de busca - vídeo)
    - [ ] Implementar:
        - [ ] insert    // insere um valor na árvore
        - [ ] get_node_count // obtém contagem de valores armazenados
        - [ ] print_values // exibe os valores na árvore, do min até o max
        - [ ] delete_tree
        - [ ] is_in_tree // retorna "true" se tal valor existir na árvore
        - [ ] get_height // retorna a altura nos nós (altura de nó único é 1)
        - [ ] get_min   // retorna o valor mínimo armazenado na árvore
        - [ ] get_max   // retorna o valor máximo armazenado na árvore
        - [ ] is_binary_search_tree
        - [ ] delete_value
        - [ ] get_successor // retorna o próximo maior valor na árvore após dado valor, -1 se não houver nenhum

- ### Memória Dinâmica (heap) / Filas Prioritárias / Memória Dinâmica Binária (heap binary)
    - visualizada como uma árvore, mas geralmente é linear no armazenamento (array, lista ligada)
    - [ ] [Heap](https://en.wikipedia.org/wiki/Heap_(data_structure)) (Memória DInâmica)
    - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction) (Introdução - vídeo)
    - [ ] [Naive Implementations (video)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations) (Implementações Ingênuas - vídeo)
    - [ ] [Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees) (Árvores Binárias - vídeo)
    - [ ] [Tree Height Remark (video)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark) (Observações sobre Altura de Árvore - vídeo)
    - [ ] [Basic Operations (video)](https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations) (Operações Básicas - vídeo)
    - [ ] [Complete Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees) (Árvores Binárias Completas - vídeo)
    - [ ] [Pseudocode (video)](https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode) (Pseudocódigo - vídeo)
    - [ ] [Heap Sort - jumps to start (video)](https://youtu.be/odNJmw5TOEE?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291) (Algoritmo de Ordenação heapsort - pula para o começo - vídeo)
    - [ ] [Heap Sort (video)](https://www.coursera.org/learn/data-structures/lecture/hSzMO/heap-sort) (Algoritmo de Ordenação heapsort - vídeo)
    - [ ] [Building a heap (video)](https://www.coursera.org/learn/data-structures/lecture/dwrOS/building-a-heap) (Construindo uma memória dinâmica (heap) - vídeo)
    - [ ] [MIT: Heaps and Heap Sort (video)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb) (MIT: Memórias Dinâmias e heapsort - vídeo)
    - [ ] [CS 61B Lecture 24: Priority Queues (video)](https://www.youtube.com/watch?v=yIUFT6AKBGE&index=24&list=PL4BBB74C7D2A1049C) (CS (Ciência da Computação) 61B Aula 24: Filas Prioritárias - vídeo)
    - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw) (BuildHeap em Tempo Linear (heap máxima))
    - [ ] Implementar uma heap máxima (max-heap):
        - [ ] insert
        - [ ] sift_up - necessário insert
        - [ ] get_max - retorna o item max (maior item), sem removê-lo
        - [ ] get_size() - retorna o número de elementos armazenados
        - [ ] is_empty() - retorna "true" se o heap não contém elementos
        - [ ] extract_max - retorna o item max (maior item), removendo ele
        - [ ] sift_down - necessário para extract_max
        - [ ] remove(i) - remove o item no índice x
        - [ ] heapify - cria um heap a partir de um array de elementos, necessário para heap_sort
        - [ ] heap_sort() - pega um array não-ordenado e o transforma em um array ordenado "in-place" (sem gerar um novo array) usando uma heap máxima (max-heap)
            - nota: usando uma heap mínima (min-heap) ao invés de uma heap máxima (max-heap) poderia salvar operações, mas duplicar o espaço necessário (não é possível fazer "in-place")

## Sorting

- [ ] Notes:
    - Implement sorts & know best case/worst case, average complexity of each:
        - no bubble sort - it's terrible - O(n^2), except when n <= 16
    - [ ] stability in sorting algorithms ("Is Quicksort stable?")
        - [Sorting Algorithm Stability](https://en.wikipedia.org/wiki/Sorting_algorithm#Stability)
        - [Stability In Sorting Algorithms](http://stackoverflow.com/questions/1517793/stability-in-sorting-algorithms)
        - [Stability In Sorting Algorithms](http://www.geeksforgeeks.org/stability-in-sorting-algorithms/)
        - [Sorting Algorithms - Stability](http://homepages.math.uic.edu/~leon/cs-mcs401-s08/handouts/stability.pdf)
    - [ ] Which algorithms can be used on linked lists? Which on arrays? Which on both?
        - I wouldn't recommend sorting a linked list, but merge sort is doable.
        - [Merge Sort For Linked List](http://www.geeksforgeeks.org/merge-sort-for-linked-list/)

- For heapsort, see Heap data structure above. Heap sort is great, but not stable.

- [ ] [Sedgewick - Mergesort (5 videos)](https://www.youtube.com/watch?v=4nKwesx_c8E&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9)
    - [ ] [1. Mergesort](https://www.youtube.com/watch?v=4nKwesx_c8E&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9&index=1)
    - [ ] [2. Bottom up Mergesort](https://www.youtube.com/watch?v=HGOIGUYjeyk&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9&index=2)
    - [ ] [3. Sorting Complexity](https://www.youtube.com/watch?v=WvU_mIWo0Ac&index=3&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9)
    - [ ] [4. Comparators](https://www.youtube.com/watch?v=7MvC1kmBza0&index=4&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9)
    - [ ] [5. Stability](https://www.youtube.com/watch?v=XD_5iINB5GI&index=5&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9)

- [ ] [Sedgewick - Quicksort (4 videos)](https://www.youtube.com/playlist?list=PLe-ggMe31CTeE3x2-nF1-toca1QpuXwE1)
    - [ ] [1. Quicksort](https://www.youtube.com/watch?v=5M5A7qPWk84&index=1&list=PLe-ggMe31CTeE3x2-nF1-toca1QpuXwE1)
    - [ ] [2. Selection](https://www.youtube.com/watch?v=CgVYfSyct_M&index=2&list=PLe-ggMe31CTeE3x2-nF1-toca1QpuXwE1)
    - [ ] [3. Duplicate Keys](https://www.youtube.com/watch?v=WBFzOYJ5ybM&index=3&list=PLe-ggMe31CTeE3x2-nF1-toca1QpuXwE1)
    - [ ] [4. System Sorts](https://www.youtube.com/watch?v=rejpZ2htBjE&index=4&list=PLe-ggMe31CTeE3x2-nF1-toca1QpuXwE1)

- [ ] UC Berkeley:
    - [ ] [CS 61B Lecture 29: Sorting I (video)](https://www.youtube.com/watch?v=EiUvYS2DT6I&list=PL4BBB74C7D2A1049C&index=29)
    - [ ] [CS 61B Lecture 30: Sorting II (video)](https://www.youtube.com/watch?v=2hTY3t80Qsk&list=PL4BBB74C7D2A1049C&index=30)
    - [ ] [CS 61B Lecture 32: Sorting III (video)](https://www.youtube.com/watch?v=Y6LOLpxg6Dc&index=32&list=PL4BBB74C7D2A1049C)
    - [ ] [CS 61B Lecture 33: Sorting V (video)](https://www.youtube.com/watch?v=qNMQ4ly43p4&index=33&list=PL4BBB74C7D2A1049C)

- [ ] [Bubble Sort (video)](https://www.youtube.com/watch?v=P00xJgWzz2c&index=1&list=PL89B61F78B552C1AB)
- [ ] [Analyzing Bubble Sort (video)](https://www.youtube.com/watch?v=ni_zk257Nqo&index=7&list=PL89B61F78B552C1AB)
- [ ] [Insertion Sort, Merge Sort (video)](https://www.youtube.com/watch?v=Kg4bqzAqRBM&index=3&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [ ] [Insertion Sort (video)](https://www.youtube.com/watch?v=c4BRHC7kTaQ&index=2&list=PL89B61F78B552C1AB)
- [ ] [Merge Sort (video)](https://www.youtube.com/watch?v=GCae1WNvnZM&index=3&list=PL89B61F78B552C1AB)
- [ ] [Quicksort (video)](https://www.youtube.com/watch?v=y_G9BkAm6B8&index=4&list=PL89B61F78B552C1AB)
- [ ] [Selection Sort (video)](https://www.youtube.com/watch?v=6nDMgr0-Yyo&index=8&list=PL89B61F78B552C1AB)

- [ ] Merge sort code:
    - [ ] [Using output array (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/sorting/mergesort.c)
    - [ ] [Using output array (Python)](https://github.com/jwasham/practice-python/blob/master/merge_sort/merge_sort.py)
    - [ ] [In-place (C++)](https://github.com/jwasham/practice-cpp/blob/master/merge_sort/merge_sort.cc)
- [ ] Quick sort code:
    - [ ] [Implementation (C)](http://www.cs.yale.edu/homes/aspnes/classes/223/examples/randomization/quick.c)
    - [ ] [Implementation (C)](https://github.com/jwasham/practice-c/blob/master/quick_sort/quick_sort.c)
    - [ ] [Implementation (Python)](https://github.com/jwasham/practice-python/blob/master/quick_sort/quick_sort.py)

- [ ] Implementar:
    - [ ] Mergesort: O(n log n) average and worst case
    - [ ] Quicksort O(n log n) average case
    - Selection sort and insertion sort are both O(n^2) average and worst case
    - For heapsort, see Heap data structure above.

- [ ] Not required, but I recommended them:
    - [ ] [Sedgewick - Radix Sorts (6 videos)](https://www.youtube.com/playlist?list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53)
        - [ ] [1. Strings in Java](https://www.youtube.com/watch?v=zRzU-FWsjNU&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=6)
        - [ ] [2. Key Indexed Counting](https://www.youtube.com/watch?v=CtgKYmXs62w&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=5)
        - [ ] [3. Least Significant Digit First String Radix Sort](https://www.youtube.com/watch?v=2pGVq_BwPKs&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=4)
        - [ ] [4. Most Significant Digit First String Radix Sort](https://www.youtube.com/watch?v=M3cYNY90R6c&index=3&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53)
        - [ ] [5. 3 Way Radix Quicksort](https://www.youtube.com/watch?v=YVl58kfE6i8&index=2&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53)
        - [ ] [6. Suffix Arrays](https://www.youtube.com/watch?v=HKPrVm5FWvg&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53&index=1)
    - [ ] [Radix Sort](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#radixSort)
    - [ ] [Radix Sort (video)](https://www.youtube.com/watch?v=xhr26ia4k38)
    - [ ] [Radix Sort, Counting Sort (linear time given constraints) (video)](https://www.youtube.com/watch?v=Nz1KZXbghj8&index=7&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [Randomization: Matrix Multiply, Quicksort, Freivalds' algorithm (video)](https://www.youtube.com/watch?v=cNB2lADK3_s&index=8&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [Sorting in Linear Time (video)](https://www.youtube.com/watch?v=pOKy3RZbSws&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=14)

As a summary, here is a visual representation of [15 sorting algorithms](https://www.youtube.com/watch?v=kPRA0W1kECg).
If you need more detail on this subject, see "Sorting" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects)

## Graphs

Graphs can be used to represent many problems in computer science, so this section is long, like trees and sorting were.

- Notes:
    - There are 4 basic ways to represent a graph in memory:
        - objects and pointers
        - adjacency matrix
        - adjacency list
        - adjacency map
    - Familiarize yourself with each representation and its pros & cons
    - BFS and DFS - know their computational complexity, their tradeoffs, and how to implement them in real code
    - When asked a question, look for a graph-based solution first, then move on if none.

- [ ] Skiena Lectures - great intro:
    - [ ] [CSE373 2012 - Lecture 11 - Graph Data Structures (video)](https://www.youtube.com/watch?v=OiXxhDrFruw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=11)
    - [ ] [CSE373 2012 - Lecture 12 - Breadth-First Search (video)](https://www.youtube.com/watch?v=g5vF8jscteo&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=12)
    - [ ] [CSE373 2012 - Lecture 13 - Graph Algorithms (video)](https://www.youtube.com/watch?v=S23W6eTcqdY&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=13)
    - [ ] [CSE373 2012 - Lecture 14 - Graph Algorithms (con't) (video)](https://www.youtube.com/watch?v=WitPBKGV0HY&index=14&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [CSE373 2012 - Lecture 15 - Graph Algorithms (con't 2) (video)](https://www.youtube.com/watch?v=ia1L30l7OIg&index=15&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [CSE373 2012 - Lecture 16 - Graph Algorithms (con't 3) (video)](https://www.youtube.com/watch?v=jgDOQq6iWy8&index=16&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)

- [ ] Graphs (review and more):

    - [ ] [6.006 Single-Source Shortest Paths Problem (video)](https://www.youtube.com/watch?v=Aa2sqUhIn-E&index=15&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [6.006 Dijkstra (video)](https://www.youtube.com/watch?v=2E7MmKv0Y24&index=16&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [6.006 Bellman-Ford (video)](https://www.youtube.com/watch?v=ozsuci5pIso&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=17)
    - [ ] [6.006 Speeding Up Dijkstra (video)](https://www.youtube.com/watch?v=CHvQ3q_gJ7E&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=18)
    - [ ] [Aduni: Graph Algorithms I - Topological Sorting, Minimum Spanning Trees, Prim's Algorithm -  Lecture 6 (video)]( https://www.youtube.com/watch?v=i_AQT_XfvD8&index=6&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
    - [ ] [Aduni: Graph Algorithms II - DFS, BFS, Kruskal's Algorithm, Union Find Data Structure - Lecture 7 (video)]( https://www.youtube.com/watch?v=ufj5_bppBsA&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=7)
    - [ ] [Aduni: Graph Algorithms III: Shortest Path - Lecture 8 (video)](https://www.youtube.com/watch?v=DiedsPsMKXc&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=8)
    - [ ] [Aduni: Graph Alg. IV: Intro to geometric algorithms - Lecture 9 (video)](https://www.youtube.com/watch?v=XIAQRlNkJAw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=9)
    - [ ] [CS 61B 2014 (starting at 58:09) (video)](https://youtu.be/dgjX4HdMI-Q?list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&t=3489)
    - [ ] [CS 61B 2014: Weighted graphs (video)](https://www.youtube.com/watch?v=aJjlQCFwylA&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=19)
    - [ ] [Greedy Algorithms: Minimum Spanning Tree (video)](https://www.youtube.com/watch?v=tKwnms5iRBU&index=16&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [Strongly Connected Components Kosaraju's Algorithm Graph Algorithm (video)](https://www.youtube.com/watch?v=RpgcYiky7uw)

- Full Coursera Course:
    - [ ] [Algorithms on Graphs (video)](https://www.coursera.org/learn/algorithms-on-graphs/home/welcome)

- I'll implement:
    - [ ] DFS with adjacency list (recursive)
    - [ ] DFS with adjacency list (iterative with stack)
    - [ ] DFS with adjacency matrix (recursive)
    - [ ] DFS with adjacency matrix (iterative with stack)
    - [ ] BFS with adjacency list
    - [ ] BFS with adjacency matrix
    - [ ] single-source shortest path (Dijkstra)
    - [ ] minimum spanning tree
    - DFS-based algorithms (see Aduni videos above):
        - [ ] check for cycle (needed for topological sort, since we'll check for cycle before starting)
        - [ ] topological sort
        - [ ] count connected components in a graph
        - [ ] list strongly connected components
        - [ ] check for bipartite graph

Você ganhará mais prática com gráficos no livro do Skiena (veja a seção de livro abaixo) e os livros da entrevista

## Even More Knowledge

- ### Recursion
    - [ ] Stanford lectures on recursion & backtracking:
        - [ ] [Lecture 8 | Programming Abstractions (video)](https://www.youtube.com/watch?v=gl3emqCuueQ&list=PLFE6E58F856038C69&index=8)
        - [ ] [Lecture 9 | Programming Abstractions (video)](https://www.youtube.com/watch?v=uFJhEPrbycQ&list=PLFE6E58F856038C69&index=9)
        - [ ] [Lecture 10 | Programming Abstractions (video)](https://www.youtube.com/watch?v=NdF1QDTRkck&index=10&list=PLFE6E58F856038C69)
        - [ ] [Lecture 11 | Programming Abstractions (video)](https://www.youtube.com/watch?v=p-gpaIGRCQI&list=PLFE6E58F856038C69&index=11)
    - when it is appropriate to use it
    - how is tail recursion better than not?
        - [ ] [What Is Tail Recursion Why Is It So Bad?](https://www.quora.com/What-is-tail-recursion-Why-is-it-so-bad)
        - [ ] [Tail Recursion (video)](https://www.youtube.com/watch?v=L1jjXGfxozc)

- ### Dynamic Programming
    - This subject can be pretty difficult, as each DP soluble problem must be defined as a recursion relation, and coming up with it can be tricky.
    - I suggest looking at many examples of DP problems until you have a solid understanding of the pattern involved.
    - [ ] vídeos:
        - the Skiena videos can be hard to follow since he sometimes uses the whiteboard, which is too small to see
        - [ ] [Skiena: CSE373 2012 - Lecture 19 - Introduction to Dynamic Programming (video)](https://youtu.be/Qc2ieXRgR0k?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1718)
        - [ ] [Skiena: CSE373 2012 - Lecture 20 - Edit Distance (video)](https://youtu.be/IsmMhMdyeGY?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=2749)
        - [ ] [Skiena: CSE373 2012 - Lecture 21 - Dynamic Programming Examples (video)](https://youtu.be/o0V9eYF4UI8?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=406)
        - [ ] [Skiena: CSE373 2012 - Lecture 22 - Applications of Dynamic Programming (video)](https://www.youtube.com/watch?v=dRbMC1Ltl3A&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=22)
        - [ ] [Simonson: Dynamic Programming 0 (starts at 59:18) (video)](https://youtu.be/J5aJEcOr6Eo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3558)
        - [ ] [Simonson: Dynamic Programming I - Lecture 11 (video)](https://www.youtube.com/watch?v=0EzHjQ_SOeU&index=11&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [Simonson: Dynamic programming II - Lecture 12 (video)](https://www.youtube.com/watch?v=v1qiRwuJU7g&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=12)
        - [ ] List of individual DP problems (each is short):
            [Dynamic Programming (video)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr)
    - [ ] Yale Lecture notes:
        - [ ] [Dynamic Programming](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#dynamicProgramming)
    - [ ] Coursera:
        - [ ] [The RNA secondary structure problem (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/80RrW/the-rna-secondary-structure-problem)
        - [ ] [A dynamic programming algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/PSonq/a-dynamic-programming-algorithm)
        - [ ] [Illustrating the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/oUEK2/illustrating-the-dp-algorithm)
        - [ ] [Running time of the DP algorithm (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/nfK2r/running-time-of-the-dp-algorithm)
        - [ ] [DP vs. recursive implementation (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/M999a/dp-vs-recursive-implementation)
        - [ ] [Global pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/UZ7o6/global-pairwise-sequence-alignment)
        - [ ] [Local pairwise sequence alignment (video)](https://www.coursera.org/learn/algorithmic-thinking-2/lecture/WnNau/local-pairwise-sequence-alignment)

- ### Object-Oriented Programming
    - [ ] [Optional: UML 2.0 Series (video)](https://www.youtube.com/watch?v=OkC7HKtiZC0&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc)
    - [ ] Object-Oriented Software Engineering: Software Dev Using UML and Java (21 videos):
        - Can skip this if you have a great grasp of OO and OO design practices.
        - [OOSE: Software Dev Using UML and Java](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
    - [ ] SOLID OOP Principles:
        - [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (video)](https://www.youtube.com/watch?v=TMuno5RZNeE)
        - [ ] [SOLID Design Patterns in C# (video)](https://www.youtube.com/playlist?list=PL8m4NUhTQU48oiGCSgCP1FiJEcg_xJzyQ)
        - [ ] [SOLID Principles (video)](https://www.youtube.com/playlist?list=PL4CE9F710017EA77A)
        - [ ] S - [Single Responsibility Principle](http://www.oodesign.com/single-responsibility-principle.html) | [Single responsibility to each Object](http://www.javacodegeeks.com/2011/11/solid-single-responsibility-principle.html)
            - [more flavor](https://docs.google.com/open?id=0ByOwmqah_nuGNHEtcU5OekdDMkk)
        - [ ] O - [Open/Closed Principal](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension for not for modification](https://en.wikipedia.org/wiki/Open/closed_principle)
            - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgN2M5MTkwM2EtNWFkZC00ZTI3LWFjZTUtNTFhZGZiYmUzODc1&hl=en)
        - [ ] L - [Liskov Substitution Principal](http://www.oodesign.com/liskov-s-substitution-principle.html) | [Base Class and Derived class follow ‘IS A’ principal](http://stackoverflow.com/questions/56860/what-is-the-liskov-substitution-principle)
            - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgNzAzZjA5ZmItNjU3NS00MzQ5LTkwYjMtMDJhNDU5ZTM0MTlh&hl=en)
        - [ ] I - [Interface segregation principle](http://www.oodesign.com/interface-segregation-principle.html) | clients should not be forced to implement interfaces they don't use
            - [Interface Segregation Principle in 5 minutes (video)](https://www.youtube.com/watch?v=3CtAfl7aXAQ)
            - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgOTViYjJhYzMtMzYxMC00MzFjLWJjMzYtOGJiMDc5N2JkYmJi&hl=en)
        - [ ] D -[Dependency Inversion principle](http://www.oodesign.com/dependency-inversion-principle.html) | Reduce the dependency In composition of objects.
            - [Why Is The Dependency Inversion Principle And Why Is It Important](http://stackoverflow.com/questions/62539/what-is-the-dependency-inversion-principle-and-why-is-it-important)
            - [more flavor](http://docs.google.com/a/cleancoder.com/viewer?a=v&pid=explorer&chrome=true&srcid=0BwhCYaYDn8EgMjdlMWIzNGUtZTQ0NC00ZjQ5LTkwYzQtZjRhMDRlNTQ3ZGMz&hl=en)

- ### Design patterns
    - [ ] [Quick UML review (video)](https://www.youtube.com/watch?v=3cmzqZzwNDM&list=PLGLfVvz_LVvQ5G-LdJ8RLqe-ndo7QITYc&index=3)
    - [ ] Learn these patterns:
        - [ ] strategy
        - [ ] singleton
        - [ ] adapter
        - [ ] prototype
        - [ ] decorator
        - [ ] visitor
        - [ ] factory, abstract factory
        - [ ] facade
        - [ ] observer
        - [ ] proxy
        - [ ] delegate
        - [ ] command
        - [ ] state
        - [ ] memento
        - [ ] iterator
        - [ ] composite
        - [ ] flyweight
    - [ ] [Chapter 6 (Part 1) - Patterns (video)](https://youtu.be/LAP2A80Ajrg?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO&t=3344)
    - [ ] [Chapter 6 (Part 2) - Abstraction-Occurrence, General Hierarchy, Player-Role, Singleton, Observer, Delegation (video)](https://www.youtube.com/watch?v=U8-PGsjvZc4&index=12&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
    - [ ] [Chapter 6 (Part 3) - Adapter, Facade, Immutable, Read-Only Interface, Proxy (video)](https://www.youtube.com/watch?v=7sduBHuex4c&index=13&list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)
    - [ ] [Video series (27 videos)](https://www.youtube.com/playlist?list=PLF206E906175C7E07)
    - [ ] [Head First Design Patterns](https://www.amazon.com/Head-First-Design-Patterns-Freeman/dp/0596007124)
        - I know the canonical book is "Design Patterns: Elements of Reusable Object-Oriented Software", but Head First is great for beginners to OO.
    - [ ] [Handy reference: 101 Design Patterns & Tips for Developers](https://sourcemaking.com/design-patterns-and-tips)
    - [ ] [Design patterns for humans](https://github.com/kamranahmedse/design-patterns-for-humans#structural-design-patterns)

- ### Combinatorics (n choose k) & Probability
    - [ ] [Math Skills: How to find Factorial, Permutation and Combination (Choose) (video)](https://www.youtube.com/watch?v=8RRo6Ti9d0U)
    - [ ] [Make School: Probability (video)](https://www.youtube.com/watch?v=sZkAAk9Wwa4)
    - [ ] [Make School: More Probability and Markov Chains (video)](https://www.youtube.com/watch?v=dNaJg-mLobQ)
    - [ ] Khan Academy:
        - Course layout:
            - [ ] [Basic Theoretical Probability](https://www.khanacademy.org/math/probability/probability-and-combinatorics-topic)
        - Just the videos - 41 (each are simple and each are short):
            - [ ] [Probability Explained (video)](https://www.youtube.com/watch?v=uzkc-qNVoOk&list=PLC58778F28211FA19)

- ### NP, NP-Complete and Approximation Algorithms
    - Know about the most famous classes of NP-complete problems, such as traveling salesman and the knapsack problem,
        and be able to recognize them when an interviewer asks you them in disguise.
    - Know what NP-complete means.
    - [ ] [Computational Complexity (video)](https://www.youtube.com/watch?v=moPtwq_cVH8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=23)
    - [ ] Simonson:
        - [ ] [Greedy Algs. II & Intro to NP Completeness (video)](https://youtu.be/qcGnJ47Smlo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=2939)
        - [ ] [NP Completeness II & Reductions (video)](https://www.youtube.com/watch?v=e0tGC6ZQdQE&index=16&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [NP Completeness III (video)](https://www.youtube.com/watch?v=fCX1BGT3wjE&index=17&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
        - [ ] [NP Completeness IV (video)](https://www.youtube.com/watch?v=NKLDp3Rch3M&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=18)
    - [ ] Skiena:
        - [ ] [CSE373 2012 - Lecture 23 - Introduction to NP-Completeness (video)](https://youtu.be/KiK5TVgXbFg?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1508)
        - [ ] [CSE373 2012 - Lecture 24 - NP-Completeness Proofs (video)](https://www.youtube.com/watch?v=27Al52X3hd4&index=24&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
        - [ ] [CSE373 2012 - Lecture 25 - NP-Completeness Challenge (video)](https://www.youtube.com/watch?v=xCPH4gwIIXM&index=25&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
    - [ ] [Complexity: P, NP, NP-completeness, Reductions (video)](https://www.youtube.com/watch?v=eHZifpgyH_4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=22)
    - [ ] [Complexity: Approximation Algorithms (video)](https://www.youtube.com/watch?v=MEz1J9wY2iM&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=24)
    - [ ] [Complexity: Fixed-Parameter Algorithms (video)](https://www.youtube.com/watch?v=4q-jmGrmxKs&index=25&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - Peter Norvig discusses near-optimal solutions to traveling salesman problem:
        - [Jupyter Notebook](http://nbviewer.jupyter.org/url/norvig.com/ipython/TSP.ipynb)
    - Pages 1048 - 1140 in CLRS if you have it.

- ### Caches
    - [ ] LRU cache:
        - [ ] [The Magic of LRU Cache (100 Days of Google Dev) (video)](https://www.youtube.com/watch?v=R5ON3iwx78M)
        - [ ] [Implementing LRU (video)](https://www.youtube.com/watch?v=bq6N7Ym81iI)
        - [ ] [LeetCode - 146 LRU Cache (C++) (video)](https://www.youtube.com/watch?v=8-FZRAjR7qU)
    - [ ] CPU cache:
        - [ ] [MIT 6.004 L15: The Memory Hierarchy (video)](https://www.youtube.com/watch?v=vjYF_fAZI5E&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-&index=24)
        - [ ] [MIT 6.004 L16: Cache Issues (video)](https://www.youtube.com/watch?v=ajgC3-pyGlk&index=25&list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-)

- ### Processes and Threads
    - [ ] Computer Science 162 - Operating Systems (25 videos):
        - for processes and threads see videos 1-11
        - [Operating Systems and System Programming (video)](https://www.youtube.com/playlist?list=PL-XXv-cvA_iBDyz-ba4yDskqMDY6A1w_c)
    - [What Is The Difference Between A Process And A Thread?](https://www.quora.com/What-is-the-difference-between-a-process-and-a-thread)
    - Covers:
        - Processes, Threads, Concurrency issues
            - difference between processes and threads
            - processes
            - threads
            - locks
            - mutexes
            - semaphores
            - monitors
            - how they work
            - deadlock
            - livelock
        - CPU activity, interrupts, context switching
        - Modern concurrency constructs with multicore processors
        - [Paging, segmentation and virtual memory (video)](https://www.youtube.com/watch?v=LKe7xK0bF7o&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=2)
        - [Interrupts (video)](https://www.youtube.com/watch?v=uFKi2-J-6II&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8&index=3)
        - [Scheduling (video)](https://www.youtube.com/watch?v=-Gu5mYdKbu4&index=4&list=PLCiOXwirraUCBE9i_ukL8_Kfg6XNv7Se8)
        - Process resource needs (memory: code, static storage, stack, heap, and also file descriptors, i/o)
        - Thread resource needs (shares above (minus stack) with other threads in the same process but each has its own pc, stack counter, registers, and stack)
        - Forking is really copy on write (read-only) until the new process writes to memory, then it does a full copy.
        - Context switching
            - How context switching is initiated by the operating system and underlying hardware
    - [ ] [threads in C++ (series - 10 videos)](https://www.youtube.com/playlist?list=PL5jc9xFGsL8E12so1wlMS0r0hTQoJL74M)
    - [ ] concurrency in Python (videos):
        - [ ] [Short series on threads](https://www.youtube.com/playlist?list=PL1H1sBF1VAKVMONJWJkmUh6_p8g4F2oy1)
        - [ ] [Python Threads](https://www.youtube.com/watch?v=Bs7vPNbB9JM)
        - [ ] [Understanding the Python GIL (2010)](https://www.youtube.com/watch?v=Obt-vMVdM8s)
            - [reference](http://www.dabeaz.com/GIL)
        - [ ] [David Beazley - Python Concurrency From the Ground Up: LIVE! - PyCon 2015](https://www.youtube.com/watch?v=MCs5OvhV9S4)
        - [ ] [Keynote David Beazley - Topics of Interest (Python Asyncio)](https://www.youtube.com/watch?v=ZzfHjytDceU)
        - [ ] [Mutex in Python](https://www.youtube.com/watch?v=0zaPs8OtyKY)

- ### Papers
    - Reading all from end to end with full comprehension will likely take more time than you have. I recommend being selective on papers and their sections.
    - [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/)
    - [ ] [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf)
        - [implemented in Go](https://godoc.org/github.com/thomas11/csp)
    - [ ] [2003: The Google File System](http://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf)
        - replaced by Colossus in 2012
    - [ ] [2004: MapReduce: Simplified Data Processing on Large Clusters]( http://static.googleusercontent.com/media/research.google.com/en//archive/mapreduce-osdi04.pdf)
        - mostly replaced by Cloud Dataflow?
    - [ ] [2006: Bigtable: A Distributed Storage System for Structured Data](https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf)
        - [An Inside Look at Google BigQuery](https://cloud.google.com/files/BigQueryTechnicalWP.pdf)
    - [ ] [2006: The Chubby Lock Service for Loosely-Coupled Distributed Systems](https://research.google.com/archive/chubby-osdi06.pdf)
    - [ ] [2007: Dynamo: Amazon’s Highly Available Key-value Store](https://www.akkadia.org/drepper/cpumemory.pdf)
        - The Dynamo paper kicked off the NoSQL revolution
    - [ ] [2007: What Every Programmer Should Know About Memory (very long, and the author encourages skipping of some sections)](http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf)
    - [ ] [2010: Dapper, a Large-Scale Distributed Systems Tracing Infrastructure](https://research.google.com/pubs/archive/36356.pdf)
    - [ ] [2010: Dremel: Interactive Analysis of Web-Scale Datasets](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36632.pdf)
    - [ ] [2012: Google's Colossus](https://www.wired.com/2012/07/google-colossus/)
        - paper not available
    - [ ] 2012: AddressSanitizer: A Fast Address Sanity Checker:
        - [paper](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/37752.pdf)
        - [video](https://www.usenix.org/conference/atc12/technical-sessions/presentation/serebryany)
    - [ ] 2013: Spanner: Google’s Globally-Distributed Database:
        - [paper](http://static.googleusercontent.com/media/research.google.com/en//archive/spanner-osdi2012.pdf)
        - [video](https://www.usenix.org/node/170855)
    - [ ] [2014: Machine Learning: The High-Interest Credit Card of Technical Debt](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43146.pdf)
    - [ ] [2015: Continuous Pipelines at Google](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43790.pdf)
    - [ ] [2015: High-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads](https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44686.pdf)
    - [ ] [2015: TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](http://download.tensorflow.org/paper/whitepaper2015.pdf )
    - [ ] [2015: How Developers Search for Code: A Case Study](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/43835.pdf)
    - [ ] [2016: Borg, Omega, and Kubernetes](http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/44843.pdf)

- ### Testing
    - To cover:
        - how unit testing works
        - what are mock objects
        - what is integration testing
        - what is dependency injection
    - [ ] [Agile Software Testing with James Bach (video)](https://www.youtube.com/watch?v=SAhJf36_u5U)
    - [ ] [Open Lecture by James Bach on Software Testing (video)](https://www.youtube.com/watch?v=ILkT_HV9DVU)
    - [ ] [Steve Freeman - Test-Driven Development (that’s not what we meant) (video)](https://vimeo.com/83960706)
        - [slides](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf)
    - [ ] [TDD is dead. Long live testing.](http://david.heinemeierhansson.com/2014/tdd-is-dead-long-live-testing.html)
    - [ ] [Is TDD dead? (video)](https://www.youtube.com/watch?v=z9quxZsLcfo)
    - [ ] [Video series (152 videos) - not all are needed (video)](https://www.youtube.com/watch?v=nzJapzxH_rE&list=PLAwxTw4SYaPkWVHeC_8aSIbSxE_NXI76g)
    - [ ] [Test-Driven Web Development with Python](http://www.obeythetestinggoat.com/pages/book.html#toc)
    - [ ] Dependency injection:
        - [ ] [video](https://www.youtube.com/watch?v=IKD2-MAkXyQ)
        - [ ] [Tao Of Testing](http://jasonpolites.github.io/tao-of-testing/ch3-1.1.html)
    - [ ] [How to write tests](http://jasonpolites.github.io/tao-of-testing/ch4-1.1.html)

- ### Scheduling
    - in an OS, how it works
    - can be gleaned from Operating System videos

- ### Implement system routines
    - understand what lies beneath the programming APIs you use
    - can you implement them?

- ### String searching & manipulations
    - [ ] [Sedgewick - Suffix Arrays (video)](https://www.youtube.com/watch?v=HKPrVm5FWvg)
    - [ ] [Sedgewick - Substring Search (videos)](https://www.youtube.com/watch?v=2LvvVFCEIv8&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=5)
        - [ ] [1. Introduction to Substring Search](https://www.youtube.com/watch?v=2LvvVFCEIv8&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=5)
        - [ ] [2. Brute-Force Substring Search](https://www.youtube.com/watch?v=CcDXwIGEXYU&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=4)
        - [ ] [3. Knuth-Morris Pratt](https://www.youtube.com/watch?v=n-7n-FDEWzc&index=3&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66)
        - [ ] [4. Boyer-Moore](https://www.youtube.com/watch?v=fI7Ch6pZXfM&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66&index=2)
        - [ ] [5. Rabin-Karp](https://www.youtube.com/watch?v=QzI0p6zDjK4&index=1&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66)
    - [ ] [Search pattern in text (video)](https://www.coursera.org/learn/data-structures/lecture/tAfHI/search-pattern-in-text)

    If you need more detail on this subject, see "String Matching" section in [Additional Detail on Some Subjects](#additional-detail-on-some-subjects)

- ### Tries
    - Note there are different kinds of tries. Some have prefixes, some don't, and some use string instead of bits
        to track the path.
    - I read through code, but will not implement.
    - [ ] [Sedgewick - Tries (3 videos)](https://www.youtube.com/playlist?list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
        - [ ] [1. R Way Tries](https://www.youtube.com/watch?v=buq2bn8x3Vo&index=3&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
        - [ ] [2. Ternary Search Tries](https://www.youtube.com/watch?v=LelV-kkYMIg&index=2&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
        - [ ] [3. Character Based Operations](https://www.youtube.com/watch?v=00YaFPcC65g&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ&index=1)
    - [ ] [Notes on Data Structures and Programming Techniques](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Tries)
    - [ ] Short course videos:
        - [ ] [Introduction To Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/08Xyf/core-introduction-to-tries)
        - [ ] [Performance Of Tries (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/PvlZW/core-performance-of-tries)
        - [ ] [Implementing A Trie (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/DFvd3/core-implementing-a-trie)
    - [ ] [The Trie: A Neglected Data Structure](https://www.toptal.com/java/the-trie-a-neglected-data-structure)
    - [ ] [TopCoder - Using Tries](https://www.topcoder.com/community/data-science/data-science-tutorials/using-tries/)
    - [ ] [Stanford Lecture (real world use case) (video)](https://www.youtube.com/watch?v=TJ8SkcUSdbU)
    - [ ] [MIT, Advanced Data Structures, Strings (can get pretty obscure about halfway through)](https://www.youtube.com/watch?v=NinWEPPrkDQ&index=16&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)

- ### Floating Point Numbers
    - [ ] simple 8-bit: [Representation of Floating Point Numbers - 1 (video - there is an error in calculations - see video description)](https://www.youtube.com/watch?v=ji3SfClm8TU)
    - [ ] 32 bit: [IEEE754 32-bit floating point binary (video)](https://www.youtube.com/watch?v=50ZYcZebIec)

- ### Unicode
    - [ ] [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets]( http://www.joelonsoftware.com/articles/Unicode.html)
    - [ ] [What Every Programmer Absolutely, Positively Needs To Know About Encodings And Character Sets To Work With Text](http://kunststube.net/encoding/)

- ### Endianness
    - [ ] [Big And Little Endian](https://www.cs.umd.edu/class/sum2003/cmsc311/Notes/Data/endian.html)
    - [ ] [Big Endian Vs Little Endian (video)](https://www.youtube.com/watch?v=JrNF0KRAlyo)
    - [ ] [Big And Little Endian Inside/Out (video)](https://www.youtube.com/watch?v=oBSuXP-1Tc0)
        - Very technical talk for kernel devs. Don't worry if most is over your head.
        - The first half is enough.

- ### Networking
    - **if you have networking experience or want to be a systems engineer, expect questions**
    - otherwise, this is just good to know
    - [ ] [Khan Academy](https://www.khanacademy.org/computing/computer-science/internet-intro)
    - [ ] [UDP and TCP: Comparison of Transport Protocols](https://www.youtube.com/watch?v=Vdc8TCESIg8)
    - [ ] [TCP/IP and the OSI Model Explained!](https://www.youtube.com/watch?v=e5DEVa9eSN0)
    - [ ] [Packet Transmission across the Internet. Networking & TCP/IP tutorial.](https://www.youtube.com/watch?v=nomyRJehhnM)
    - [ ] [HTTP](https://www.youtube.com/watch?v=WGJrLqtX7As)
    - [ ] [SSL and HTTPS](https://www.youtube.com/watch?v=S2iBR2ZlZf0)
    - [ ] [SSL/TLS](https://www.youtube.com/watch?v=Rp3iZUvXWlM)
    - [ ] [HTTP 2.0](https://www.youtube.com/watch?v=E9FxNzv1Tr8)
    - [ ] [Video Series (21 videos)](https://www.youtube.com/playlist?list=PLEbnTDJUr_IegfoqO4iPnPYQui46QqT0j)
    - [ ] [Subnetting Demystified - Part 5 CIDR Notation](https://www.youtube.com/watch?v=t5xYI0jzOf4)
    - [ ] Sockets:
        - [ ] [Java - Sockets - Introduction (video)](https://www.youtube.com/watch?v=6G_W54zuadg&t=6s)
        - [ ] [Socket Programming (video)](https://www.youtube.com/watch?v=G75vN2mnJeQ)

## System Design, Scalability, Data Handling
- **You can expect system design questions if you have 4+ years of experience.**
- Scalability and System Design are very large topics with many topics and resources, since
      there is a lot to consider when designing a software/hardware system that can scale.
      Expect to spend quite a bit of time on this.
- Considerations:
    - scalability
        - Distill large data sets to single values
        - Transform one data set to another
        - Handling obscenely large amounts of data
    - system design
        - features sets
        - interfaces
        - class hierarchies
        - designing a system under certain constraints
        - simplicity and robustness
        - tradeoffs
        - performance analysis and optimization
- [ ] **START HERE**: [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- [ ] [How Do I Prepare To Answer Design Questions In A Technical Inverview?](https://www.quora.com/How-do-I-prepare-to-answer-design-questions-in-a-technical-interview?redirected_qid=1500023)
- [ ] [8 Things You Need to Know Before a System Design Interview](http://blog.gainlo.co/index.php/2015/10/22/8-things-you-need-to-know-before-system-design-interviews/)
- [ ] [Algorithm design](http://www.hiredintech.com/algorithm-design/)
- [ ] [Database Normalization - 1NF, 2NF, 3NF and 4NF (video)](https://www.youtube.com/watch?v=UrYLYV7WSHM)
- [ ] [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - There are a lot of resources in this one. Look through the articles and examples. I put some of them below.
- [ ] [How to ace a systems design interview](http://www.palantir.com/2011/10/how-to-rock-a-systems-design-interview/)
- [ ] [Numbers Everyone Should Know](http://everythingisdata.wordpress.com/2009/10/17/numbers-everyone-should-know/)
- [ ] [How long does it take to make a context switch?](http://blog.tsunanet.net/2010/11/how-long-does-it-take-to-make-context.html)
- [ ] [Transactions Across Datacenters (video)](https://www.youtube.com/watch?v=srOgpXECblk)
- [ ] [A plain English introduction to CAP Theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem/)
- [ ] Paxos Consensus algorithm:
    - [short video](https://www.youtube.com/watch?v=s8JqcZtvnsM)
    - [extended video with use case and multi-paxos](https://www.youtube.com/watch?v=JEpsBg0AO6o)
    - [paper](http://research.microsoft.com/en-us/um/people/lamport/pubs/paxos-simple.pdf)
- [ ] [Consistent Hashing](http://www.tom-e-white.com/2007/11/consistent-hashing.html)
- [ ] [NoSQL Patterns](http://horicky.blogspot.com/2009/11/nosql-patterns.html)
- [ ] Scalability:
    - [ ] [Great overview (video)](https://www.youtube.com/watch?v=-W9F__D3oY4)
    - [ ] Short series:
        - [Clones](http://www.lecloud.net/post/7295452622/scalability-for-dummies-part-1-clones)
        - [Database](http://www.lecloud.net/post/7994751381/scalability-for-dummies-part-2-database)
        - [Cache](http://www.lecloud.net/post/9246290032/scalability-for-dummies-part-3-cache)
        - [Asynchronism](http://www.lecloud.net/post/9699762917/scalability-for-dummies-part-4-asynchronism)
    - [ ] [Scalable Web Architecture and Distributed Systems](http://www.aosabook.org/en/distsys.html)
    - [ ] [Fallacies of Distributed Computing Explained](https://pages.cs.wisc.edu/~zuyu/files/fallacies.pdf)
    - [ ] [Pragmatic Programming Techniques](http://horicky.blogspot.com/2010/10/scalable-system-design-patterns.html)
        - [extra: Google Pregel Graph Processing](http://horicky.blogspot.com/2010/07/google-pregel-graph-processing.html)
    - [ ] [Jeff Dean - Building Software Systems At Google and Lessons Learned (video)](https://www.youtube.com/watch?v=modXC5IWTJI)
    - [ ] [Introduction to Architecting Systems for Scale](http://lethain.com/introduction-to-architecting-systems-for-scale/)
    - [ ] [Scaling mobile games to a global audience using App Engine and Cloud Datastore (video)](https://www.youtube.com/watch?v=9nWyWwY2Onc)
    - [ ] [How Google Does Planet-Scale Engineering for Planet-Scale Infra (video)](https://www.youtube.com/watch?v=H4vMcD7zKM0)
    - [ ] [The Importance of Algorithms](https://www.topcoder.com/community/data-science/data-science-tutorials/the-importance-of-algorithms/)
    - [ ] [Sharding](http://highscalability.com/blog/2009/8/6/an-unorthodox-approach-to-database-design-the-coming-of-the.html)
    - [ ] [Scale at Facebook (2009)](https://www.infoq.com/presentations/Scale-at-Facebook)
    - [ ] [Scale at Facebook (2012), "Building for a Billion Users" (video)](https://www.youtube.com/watch?v=oodS71YtkGU)
    - [ ] [Engineering for the Long Game - Astrid Atkinson Keynote(video)](https://www.youtube.com/watch?v=p0jGmgIrf_M&list=PLRXxvay_m8gqVlExPC5DG3TGWJTaBgqSA&index=4)
    - [ ] [7 Years Of YouTube Scalability Lessons In 30 Minutes](http://highscalability.com/blog/2012/3/26/7-years-of-youtube-scalability-lessons-in-30-minutes.html)
        - [video](https://www.youtube.com/watch?v=G-lGCC4KKok)
    - [ ] [How PayPal Scaled To Billions Of Transactions Daily Using Just 8VMs](http://highscalability.com/blog/2016/8/15/how-paypal-scaled-to-billions-of-transactions-daily-using-ju.html)
    - [ ] [How to Remove Duplicates in Large Datasets](https://blog.clevertap.com/how-to-remove-duplicates-in-large-datasets/)
    - [ ] [A look inside Etsy's scale and engineering culture with Jon Cowie (video)](https://www.youtube.com/watch?v=3vV4YiqKm1o)
    - [ ] [What Led Amazon to its Own Microservices Architecture](http://thenewstack.io/led-amazon-microservices-architecture/)
    - [ ] [To Compress Or Not To Compress, That Was Uber's Question](https://eng.uber.com/trip-data-squeeze/)
    - [ ] [Asyncio Tarantool Queue, Get In The Queue](http://highscalability.com/blog/2016/3/3/asyncio-tarantool-queue-get-in-the-queue.html)
    - [ ] [When Should Approximate Query Processing Be Used?](http://highscalability.com/blog/2016/2/25/when-should-approximate-query-processing-be-used.html)
    - [ ] [Google's Transition From Single Datacenter, To Failover, To A Native Multihomed Architecture]( http://highscalability.com/blog/2016/2/23/googles-transition-from-single-datacenter-to-failover-to-a-n.html)
    - [ ] [Spanner](http://highscalability.com/blog/2012/9/24/google-spanners-most-surprising-revelation-nosql-is-out-and.html)
    - [ ] [Egnyte Architecture: Lessons Learned In Building And Scaling A Multi Petabyte Distributed System](http://highscalability.com/blog/2016/2/15/egnyte-architecture-lessons-learned-in-building-and-scaling.html)
    - [ ] [Machine Learning Driven Programming: A New Programming For A New World](http://highscalability.com/blog/2016/7/6/machine-learning-driven-programming-a-new-programming-for-a.html)
    - [ ] [The Image Optimization Technology That Serves Millions Of Requests Per Day](http://highscalability.com/blog/2016/6/15/the-image-optimization-technology-that-serves-millions-of-re.html)
    - [ ] [A Patreon Architecture Short](http://highscalability.com/blog/2016/2/1/a-patreon-architecture-short.html)
    - [ ] [Tinder: How Does One Of The Largest Recommendation Engines Decide Who You'll See Next?](http://highscalability.com/blog/2016/1/27/tinder-how-does-one-of-the-largest-recommendation-engines-de.html)
    - [ ] [Design Of A Modern Cache](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
    - [ ] [Live Video Streaming At Facebook Scale](http://highscalability.com/blog/2016/1/13/live-video-streaming-at-facebook-scale.html)
    - [ ] [A Beginner's Guide To Scaling To 11 Million+ Users On Amazon's AWS](http://highscalability.com/blog/2016/1/11/a-beginners-guide-to-scaling-to-11-million-users-on-amazons.html)
    - [ ] [How Does The Use Of Docker Effect Latency?](http://highscalability.com/blog/2015/12/16/how-does-the-use-of-docker-effect-latency.html)
    - [ ] [Does AMP Counter An Existential Threat To Google?](http://highscalability.com/blog/2015/12/14/does-amp-counter-an-existential-threat-to-google.html)
    - [ ] [A 360 Degree View Of The Entire Netflix Stack](http://highscalability.com/blog/2015/11/9/a-360-degree-view-of-the-entire-netflix-stack.html)
    - [ ] [Latency Is Everywhere And It Costs You Sales - How To Crush It](http://highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it)
    - [ ] [Serverless (very long, just need the gist)](http://martinfowler.com/articles/serverless.html)
    - [ ] [What Powers Instagram: Hundreds of Instances, Dozens of Technologies](http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances)
    - [ ] [Cinchcast Architecture - Producing 1,500 Hours Of Audio Every Day](http://highscalability.com/blog/2012/7/16/cinchcast-architecture-producing-1500-hours-of-audio-every-d.html)
    - [ ] [Justin.Tv's Live Video Broadcasting Architecture](http://highscalability.com/blog/2010/3/16/justintvs-live-video-broadcasting-architecture.html)
    - [ ] [Playfish's Social Gaming Architecture - 50 Million Monthly Users And Growing](http://highscalability.com/blog/2010/9/21/playfishs-social-gaming-architecture-50-million-monthly-user.html)
    - [ ] [TripAdvisor Architecture - 40M Visitors, 200M Dynamic Page Views, 30TB Data](http://highscalability.com/blog/2011/6/27/tripadvisor-architecture-40m-visitors-200m-dynamic-page-view.html)
    - [ ] [PlentyOfFish Architecture](http://highscalability.com/plentyoffish-architecture)
    - [ ] [Salesforce Architecture - How They Handle 1.3 Billion Transactions A Day](http://highscalability.com/blog/2013/9/23/salesforce-architecture-how-they-handle-13-billion-transacti.html)
    - [ ] [ESPN's Architecture At Scale - Operating At 100,000 Duh Nuh Nuhs Per Second](http://highscalability.com/blog/2013/11/4/espns-architecture-at-scale-operating-at-100000-duh-nuh-nuhs.html)
    - [ ] See "Messaging, Serialization, and Queueing Systems" way below for info on some of the technologies that can glue services together
    - [ ] Twitter:
        - [O'Reilly MySQL CE 2011: Jeremy Cole, "Big and Small Data at @Twitter" (video)](https://www.youtube.com/watch?v=5cKTP36HVgI)
        - [Timelines at Scale](https://www.infoq.com/presentations/Twitter-Timeline-Scalability)
    - For even more, see "Mining Massive Datasets" video series in the Video Series section.
- [ ] Practicing the system design process: Here are some ideas to try working through on paper, each with some documentation on how it was handled in the real world:
    - review: [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
    - [cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/system-design.pdf)
    - flow:
        1. Understand the problem and scope:
            - define the use cases, with interviewer's help
            - suggest additional features
            - remove items that interviewer deems out of scope
            - assume high availability is required, add as a use case
        2. Think about constraints:
            - ask how many requests per month
            - ask how many requests per second (they may volunteer it or make you do the math)
            - estimate reads vs. writes percentage
            - keep 80/20 rule in mind when estimating
            - how much data written per second
            - total storage required over 5 years
            - how much data read per second
        3. Abstract design:
            - layers (service, data, caching)
            - infrastructure: load balancing, messaging
            - rough overview of any key algorithm that drives the service
            - consider bottlenecks and determine solutions
    - Exercises:
        - [Design a CDN network: old article](http://repository.cmu.edu/cgi/viewcontent.cgi?article=2112&context=compsci)
        - [Design a random unique ID generation system](https://blog.twitter.com/2010/announcing-snowflake)
        - [Design an online multiplayer card game](http://www.indieflashblog.com/how-to-create-an-asynchronous-multiplayer-game.html)
        - [Design a key-value database](http://www.slideshare.net/dvirsky/introduction-to-redis)
        - [Design a picture sharing system](http://highscalability.com/blog/2011/12/6/instagram-architecture-14-million-users-terabytes-of-photos.html)
        - [Design a recommendation system](http://ijcai13.org/files/tutorial_slides/td3.pdf)
        - [Design a URL-shortener system: copied from above](http://www.hiredintech.com/system-design/the-system-design-process/)
        - [Design a cache system](https://www.adayinthelifeof.nl/2011/02/06/memcache-internals/)

---

## Final Review

    Essa seção terá vídeos mais curtos que você pode assistir rapidamente para revisar a maioria dos conceitos importantes.
    É legal se você quiser dar uma refrescada na memória.

- [ ] Series of 2-3 minutes short subject videos (23 videos)
    - [Videos](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22)
- [ ] Series of 2-5 minutes short subject videos - Michael Sambol (18 videos):
    - [Videos](https://www.youtube.com/channel/UCzDJwLWoYCUQowF_nG3m5OQ)
- [ ] [Sedgewick Videos - Algorithms I](https://www.youtube.com/user/algorithmscourses/playlists?shelf_id=2&view=50&sort=dd)
    - [ ] [01. Union-Find](https://www.youtube.com/watch?v=8mYfZeHtdNc&list=PLe-ggMe31CTexoNYnMhbHaWhQ0dvcy43t)
    - [ ] [02. Analysis of Algorithms](https://www.youtube.com/watch?v=ZN-nFW0mEpg&list=PLe-ggMe31CTf0_bkOhh7sa5uqeppp3Sr0)
    - [ ] [03. Stacks and Queues](https://www.youtube.com/watch?v=TIC1gappbP8&list=PLe-ggMe31CTe-9jhnj3P_3mmrCh0A7iHh)
    - [ ] [04. Elementary Sorts](https://www.youtube.com/watch?v=CD2AL6VO0ak&list=PLe-ggMe31CTe_5WhGV0F--7CK8MoRUqBd)
    - [ ] [05. Mergesort](https://www.youtube.com/watch?v=4nKwesx_c8E&list=PLe-ggMe31CTeunC6GZHFBmQx7EKtjbGf9)
    - [ ] [06. Quicksort](https://www.youtube.com/watch?v=5M5A7qPWk84&list=PLe-ggMe31CTeE3x2-nF1-toca1QpuXwE1)
    - [ ] [07. Priority Queues](https://www.youtube.com/watch?v=G9TMe0KC0w0&list=PLe-ggMe31CTducy9LDiGVkdSv0NfiRwn5)
    - [ ] [08. Elementary Symbol Tables](https://www.youtube.com/watch?v=up_nlilw3ac&list=PLe-ggMe31CTc3a8nKRDxFZZrWrBvkc9SG)
    - [ ] [09. Balanced Search Trees](https://www.youtube.com/watch?v=qC1BLLPK_5w&list=PLe-ggMe31CTf7jHH_mFT50kayjCEA6Rhu)
    - [ ] [10. Geometric Applications of BST](https://www.youtube.com/watch?v=Wl30aGAp6TY&list=PLe-ggMe31CTdBsRIw0hXln0hilRs-DqAx)
    - [ ] [11. Hash Tables](https://www.youtube.com/watch?v=QA8fJGO-i9o&list=PLe-ggMe31CTcKxIRGqqThMts2eHtSrf11)
- [ ] [Sedgewick Videos - Algorithms II](https://www.youtube.com/user/algorithmscourses/playlists?flow=list&shelf_id=3&view=50)
    - [ ] [01. Undirected Graphs](https://www.youtube.com/watch?v=GmVhD-mmMBg&list=PLe-ggMe31CTc0zDzANxl4I2MhMoRVlbRM)
    - [ ] [02. Directed Graphs](https://www.youtube.com/watch?v=_z-JsVaUS40&list=PLe-ggMe31CTcEwaU8a1P1Gd95A77HV85K)
    - [ ] [03. Minimum Spanning Trees](https://www.youtube.com/watch?v=t8fNk9tfVYY&list=PLe-ggMe31CTceUZxDesGfHGLE7kcSafqj)
    - [ ] [04. Shortest Paths](https://www.youtube.com/watch?v=HoGSiB7tSeI&list=PLe-ggMe31CTePpG3jbeOTsnGUGZDKxgZD)
    - [ ] [05. Maximum Flow](https://www.youtube.com/watch?v=rYIKlFstBqE&list=PLe-ggMe31CTduQ68XQ-sVj32wYJIspTma)
    - [ ] [06. Radix Sorts](https://www.youtube.com/watch?v=HKPrVm5FWvg&list=PLe-ggMe31CTcNvUX9E3tQeM6ntrdR8e53)
    - [ ] [07. Tries](https://www.youtube.com/watch?v=00YaFPcC65g&list=PLe-ggMe31CTe9IyG9MB8vt5xUJeYgOYRQ)
    - [ ] [08. Substring Search](https://www.youtube.com/watch?v=QzI0p6zDjK4&list=PLe-ggMe31CTdAdjXB3lIuf2maubzo9t66)
    - [ ] [09. Regular Expressions](https://www.youtube.com/watch?v=TQWNQsJSPnk&list=PLe-ggMe31CTetTlJWouM42fyttyKPgSDh)
    - [ ] [10. Data Compression](https://www.youtube.com/watch?v=at9tjpxcBh8&list=PLe-ggMe31CTciifRRo6yY0Yt0mzgIXXVZ)
    - [ ] [11. Reductions](https://www.youtube.com/watch?v=Ow5x-ooMGv8&list=PLe-ggMe31CTe_yliW5vc3yO-dj1LSSDyF)
    - [ ] [12. Linear Programming](https://www.youtube.com/watch?v=rWhcLyiLZLA&list=PLe-ggMe31CTdy6dKzMgkWFuTTN1H8B-E1)
    - [ ] [13. Intractability](https://www.youtube.com/watch?v=6qcaaDp4cdQ&list=PLe-ggMe31CTcZCjluBHw53e_ek2k9Kn-S)

---

## Coding Question Practice

Now that you know all the computer science topics above, it's time to practice answering coding problems.

**Coding question practice is not about memorizing answers to programming problems.**

Why you need to practice doing programming problems:
- problem recognition, and where the right data structures and algorithms fit in
- gathering requirements for the problem
- talking your way through the problem like you will in the interview
- coding on a whiteboard or paper, not a computer
- coming up with time and space complexity for your solutions
- testing your solutions

There is a great intro for methodical, communicative problem solving in an interview. You'll get this from the programming
interview books, too, but I found this outstanding:
[Algorithm design canvas](http://www.hiredintech.com/algorithm-design/)

No whiteboard at home? That makes sense. I'm a weirdo and have a big whiteboard. Instead of a whiteboard, pick up a
large drawing pad from an art store. You can sit on the couch and practice. This is my "sofa whiteboard".
I added the pen in the photo for scale. If you use a pen, you'll wish you could erase. Gets messy quick.

![my sofa whiteboard](https://dng5l3qzreal6.cloudfront.net/2016/Oct/art_board_sm_2-1476233630368.jpg)

Supplemental:

- [Mathematics for Topcoders](https://www.topcoder.com/community/data-science/data-science-tutorials/mathematics-for-topcoders/)
- [Dynamic Programming – From Novice to Advanced](https://www.topcoder.com/community/data-science/data-science-tutorials/dynamic-programming-from-novice-to-advanced/)
- [MIT Interview Materials](https://web.archive.org/web/20160906124824/http://courses.csail.mit.edu/iap/interview/materials.php)
- [Exercises for getting better at a given language](http://exercism.io/languages)

**Read and Do Programming Problems (in this order):**

- [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html)
    - answers in C, C++ and Java
- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/)
    - answers in Java

See [Book List above](#book-list)

## Coding exercises/challenges

Once you've learned your brains out, put those brains to work.
Take coding challenges every day, as many as you can.

- [ ] [How to Find a Solution](https://www.topcoder.com/community/data-science/data-science-tutorials/how-to-find-a-solution/)
- [ ] [How to Dissect a Topcoder Problem Statement](https://www.topcoder.com/community/data-science/data-science-tutorials/how-to-dissect-a-topcoder-problem-statement/)

Coding Interview Question Videos:
- [IDeserve (88 videos)](https://www.youtube.com/watch?v=NBcqBddFbZw&list=PLamzFoFxwoNjPfxzaWqs7cZGsPYy0x_gI)
- [Tushar Roy (5 playlists)](https://www.youtube.com/user/tusharroy2525/playlists?shelf_id=2&view=50&sort=dd)

Challenge sites:
- [LeetCode](https://leetcode.com/)
- [TopCoder](https://www.topcoder.com/)
- [Project Euler (math-focused)](https://projecteuler.net/index.php?section=problems)
- [Codewars](http://www.codewars.com)
- [HackerRank](https://www.hackerrank.com/)
- [Codility](https://codility.com/programmers/)
- [InterviewCake](https://www.interviewcake.com/)
- [Geeks for Geeks](http://www.geeksforgeeks.org/)
- [InterviewBit](https://www.interviewbit.com/invite/icjf)
- [Sphere Online Judge (spoj)](http://www.spoj.com/)

Mock Interviews:
- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/)
- [Pramp: Mock interviews from/with peers](https://www.pramp.com/)
- [Refdash: Mock interviews](https://refdash.com/)

## Once you're closer to the interview

- [ ] Cracking The Coding Interview Set 2 (videos):
    - [Cracking The Code Interview](https://www.youtube.com/watch?v=4NIb9l3imAo)
    - [Cracking the Coding Interview - Fullstack Speaker Series](https://www.youtube.com/watch?v=Eg5-tdAwclo)
    - [Ask Me Anything: Gayle Laakmann McDowell (author of Cracking the Coding Interview)](https://www.youtube.com/watch?v=1fqxMuPmGak)

## Your Resume

- See Resume prep items in Cracking The Coding Interview and back of Programming Interviews Exposed


## Be thinking of for when the interview comes

Think of about 20 interview questions you'll get, along with the lines of the items below. Have 2-3 answers for each.
Have a story, not just data, about something you accomplished.

- Why do you want this job?
- What's a tough problem you've solved?
- Biggest challenges faced?
- Best/worst designs seen?
- Ideas for improving an existing product.
- How do you work best, as an individual and as part of a team?
- Which of your skills or experiences would be assets in the role and why?
- What did you most enjoy at [job x / project y]?
- What was the biggest challenge you faced at [job x / project y]?
- What was the hardest bug you faced at [job x / project y]?
- What did you learn at [job x / project y]?
- What would you have done better at [job x / project y]?

## Have questions for the interviewer

    Some of mine (I already may know answer to but want their opinion or team perspective):

- How large is your team?
- What does your dev cycle look like? Do you do waterfall/sprints/agile?
- Are rushes to deadlines common? Or is there flexibility?
- How are decisions made in your team?
- How many meetings do you have per week?
- Do you feel your work environment helps you concentrate?
- What are you working on?
- What do you like about it?
- What is the work life like?

## Once You've Got The Job

Congratulations!

Keep learning.

You're never really done.

---

    *****************************************************************************************************
    *****************************************************************************************************

    Everything below this point is optional.
    By studying these, you'll get greater exposure to more CS concepts, and will be better prepared for
    any software engineering job. You'll be a much more well-rounded software engineer.

    *****************************************************************************************************
    *****************************************************************************************************

---

## Additional Books

- [ ] [The Unix Programming Environment](http://product.half.ebay.com/The-UNIX-Programming-Environment-by-Brian-W-Kernighan-and-Rob-Pike-1983-Other/54385&tg=info)
    - an oldie but a goodie
- [ ] [The Linux Command Line: A Complete Introduction](https://www.amazon.com/dp/1593273894/)
    - a modern option
- [ ] [TCP/IP Illustrated Series](https://en.wikipedia.org/wiki/TCP/IP_Illustrated)
- [ ] [Head First Design Patterns](https://www.amazon.com/gp/product/0596007124/)
    - a gentle introduction to design patterns
- [ ] [Design Patterns: Elements of Reusable Object-Oriente​d Software](https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612)
    - aka the "Gang Of Four" book, or GOF
    - the canonical design patterns book
- [ ] [UNIX and Linux System Administration Handbook, 4th Edition](https://www.amazon.com/UNIX-Linux-System-Administration-Handbook/dp/0131480057/)

## Additional Learning

These topics will likely not come up in an interview, but I added them to help you become a well-rounded
software engineer, and to be aware of certain technologies and algorithms, so you'll have a bigger toolbox.

- ### Compilers
    - [ ] [How a Compiler Works in ~1 minute (video)](https://www.youtube.com/watch?v=IhC7sdYe-Jg)
    - [ ] [Harvard CS50 - Compilers (video)](https://www.youtube.com/watch?v=CSZLNYF4Klo)
    - [ ] [C++ (video)](https://www.youtube.com/watch?v=twodd1KFfGk)
    - [ ] [Understanding Compiler Optimization (C++) (video)](https://www.youtube.com/watch?v=FnGCDLhaxKU)

- ### Emacs and vi(m)
    - Familiarize yourself with a unix-based code editor
    - vi(m):
        - [Editing With vim 01 - Installation, Setup, and The Modes (video)](https://www.youtube.com/watch?v=5givLEMcINQ&index=1&list=PL13bz4SHGmRxlZVmWQ9DvXo1fEg4UdGkr)
        - [VIM Adventures](http://vim-adventures.com/)
        - set of 4 videos:
            - [The vi/vim editor - Lesson 1](https://www.youtube.com/watch?v=SI8TeVMX8pk)
            - [The vi/vim editor - Lesson 2](https://www.youtube.com/watch?v=F3OO7ZIOaJE)
            - [The vi/vim editor - Lesson 3](https://www.youtube.com/watch?v=ZYEccA_nMaI)
            - [The vi/vim editor - Lesson 4](https://www.youtube.com/watch?v=1lYD5gwgZIA)
        - [Using Vi Instead of Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Using_Vi_instead_of_Emacs)
    - emacs:
        - [Basics Emacs Tutorial (video)](https://www.youtube.com/watch?v=hbmV1bnQ-i0)
        - set of 3 (videos):
            - [Emacs Tutorial (Beginners) -Part 1- File commands, cut/copy/paste, cursor commands](https://www.youtube.com/watch?v=ujODL7MD04Q)
            - [Emacs Tutorial (Beginners) -Part 2- Buffer management, search, M-x grep and rgrep modes](https://www.youtube.com/watch?v=XWpsRupJ4II)
            - [Emacs Tutorial (Beginners) -Part 3- Expressions, Statements, ~/.emacs file and packages](https://www.youtube.com/watch?v=paSgzPso-yc)
        - [Evil Mode: Or, How I Learned to Stop Worrying and Love Emacs (video)](https://www.youtube.com/watch?v=JWD1Fpdd4Pc)
        - [Writing C Programs With Emacs](http://www.cs.yale.edu/homes/aspnes/classes/223/notes.html#Writing_C_programs_with_Emacs)
        - [(maybe) Org Mode In Depth: Managing Structure (video)](https://www.youtube.com/watch?v=nsGYet02bEk)

- ### Unix command line tools
    - I filled in the list below from good tools.
    - [ ] bash
    - [ ] cat
    - [ ] grep
    - [ ] sed
    - [ ] awk
    - [ ] curl or wget
    - [ ] sort
    - [ ] tr
    - [ ] uniq
    - [ ] [strace](https://en.wikipedia.org/wiki/Strace)
    - [ ] [tcpdump](https://danielmiessler.com/study/tcpdump/)

- ### Information theory (videos)
    - [ ] [Khan Academy](https://www.khanacademy.org/computing/computer-science/informationtheory)
    - [ ] more about Markov processes:
        - [ ] [Core Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/waxgx/core-markov-text-generation)
        - [ ] [Core Implementing Markov Text Generation](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/gZhiC/core-implementing-markov-text-generation)
        - [ ] [Project = Markov Text Generation Walk Through](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/EUjrq/project-markov-text-generation-walk-through)
    - See more in MIT 6.050J Information and Entropy series below.

- ### Parity & Hamming Code (videos)
    - [ ] [Intro](https://www.youtube.com/watch?v=q-3BctoUpHE)
    - [ ] [Parity](https://www.youtube.com/watch?v=DdMcAUlxh1M)
    - [ ] Hamming Code:
        - [Error detection](https://www.youtube.com/watch?v=1A_NcXxdoCc)
        - [Error correction](https://www.youtube.com/watch?v=JAMLuxdHH8o)
    - [ ] [Error Checking](https://www.youtube.com/watch?v=wbH2VxzmoZk)

- ### Entropy
    - also see videos below
    - make sure to watch information theory videos first
    - [ ] [Information Theory, Claude Shannon, Entropy, Redundancy, Data Compression & Bits (video)](https://youtu.be/JnJq3Py0dyM?t=176)

- ### Cryptography
    - also see videos below
    - make sure to watch information theory videos first
    - [ ] [Khan Academy Series](https://www.khanacademy.org/computing/computer-science/cryptography)
    - [ ] [Cryptography: Hash Functions](https://www.youtube.com/watch?v=KqqOXndnvic&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=30)
    - [ ] [Cryptography: Encryption](https://www.youtube.com/watch?v=9TNI2wHmaeI&index=31&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

- ### Compression
    - make sure to watch information theory videos first
    - [ ] Computerphile (videos):
        - [ ] [Compression](https://www.youtube.com/watch?v=Lto-ajuqW3w)
        - [ ] [Entropy in Compression](https://www.youtube.com/watch?v=M5c_RFKVkko)
        - [ ] [Upside Down Trees (Huffman Trees)](https://www.youtube.com/watch?v=umTbivyJoiI)
        - [ ] [EXTRA BITS/TRITS - Huffman Trees](https://www.youtube.com/watch?v=DV8efuB3h2g)
        - [ ] [Elegant Compression in Text (The LZ 77 Method)](https://www.youtube.com/watch?v=goOa3DGezUA)
        - [ ] [Text Compression Meets Probabilities](https://www.youtube.com/watch?v=cCDCfoHTsaU)
    - [ ] [Compressor Head videos](https://www.youtube.com/playlist?list=PLOU2XLYxmsIJGErt5rrCqaSGTMyyqNt2H)
    - [ ] [(optional) Google Developers Live: GZIP is not enough!](https://www.youtube.com/watch?v=whGwm0Lky2s)

- ### Computer Security
    - [MIT (23 videos)](https://www.youtube.com/playlist?list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Introduction, Threat Models](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Control Hijacking Attacks](https://www.youtube.com/watch?v=6bwzNg5qQ0o&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=2)
        - [ ] [Buffer Overflow Exploits and Defenses](https://www.youtube.com/watch?v=drQyrzRoRiA&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=3)
        - [ ] [Privilege Separation](https://www.youtube.com/watch?v=6SIJmoE9L9g&index=4&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Capabilities](https://www.youtube.com/watch?v=8VqTSY-11F4&index=5&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Sandboxing Native Code](https://www.youtube.com/watch?v=VEV74hwASeU&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh&index=6)
        - [ ] [Web Security Model](https://www.youtube.com/watch?v=chkFBigodIw&index=7&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Securing Web Applications](https://www.youtube.com/watch?v=EBQIGy1ROLY&index=8&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Symbolic Execution](https://www.youtube.com/watch?v=yRVZPvHYHzw&index=9&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Network Security](https://www.youtube.com/watch?v=SIEVvk3NVuk&index=11&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Network Protocols](https://www.youtube.com/watch?v=QOtA76ga_fY&index=12&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)
        - [ ] [Side-Channel Attacks](https://www.youtube.com/watch?v=PuVMkSEcPiI&index=15&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)

- ### Garbage collection
    - [ ] [Garbage collection (Java); Augmenting data str (video)](https://www.youtube.com/watch?v=StdfeXaKGEc&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=25)
    - [ ] [Compilers (video)](https://www.youtube.com/playlist?list=PLO9y7hOkmmSGTy5z6HZ-W4k2y8WXF7Bff)
    - [ ] [GC in Python (video)](https://www.youtube.com/watch?v=iHVs_HkjdmI)
    - [ ] [Deep Dive Java: Garbage Collection is Good!](https://www.infoq.com/presentations/garbage-collection-benefits)
    - [ ] [Deep Dive Python: Garbage Collection in CPython (video)](https://www.youtube.com/watch?v=P-8Z0-MhdQs&list=PLdzf4Clw0VbOEWOS_sLhT_9zaiQDrS5AR&index=3)

- ### Parallel Programming
    - [ ] [Coursera (Scala)](https://www.coursera.org/learn/parprog1/home/week/1)
    - [ ] [Efficient Python for High Performance Parallel Computing (video)](https://www.youtube.com/watch?v=uY85GkaYzBk)

- ### Messaging, Serialization, and Queueing Systems
    - [ ] [Thrift](https://thrift.apache.org/)
        - [Tutorial](http://thrift-tutorial.readthedocs.io/en/latest/intro.html)
    - [ ] [Protocol Buffers](https://developers.google.com/protocol-buffers/)
        - [Tutorials](https://developers.google.com/protocol-buffers/docs/tutorials)
    - [ ] [gRPC](http://www.grpc.io/)
        - [gRPC 101 for Java Developers (video)](https://www.youtube.com/watch?v=5tmPvSe7xXQ&list=PLcTqM9n_dieN0k1nSeN36Z_ppKnvMJoly&index=1)
    - [ ] [Redis](http://redis.io/)
        - [Tutorial](http://try.redis.io/)
    - [ ] [Amazon SQS (queue)](https://aws.amazon.com/sqs/)
    - [ ] [Amazon SNS (pub-sub)](https://aws.amazon.com/sns/)
    - [ ] [RabbitMQ](https://www.rabbitmq.com/)
        - [Get Started](https://www.rabbitmq.com/getstarted.html)
    - [ ] [Celery](http://www.celeryproject.org/)
        - [First Steps With Celery](http://docs.celeryproject.org/en/latest/getting-started/first-steps-with-celery.html)
    - [ ] [ZeroMQ](http://zeromq.org/)
        - [Intro - Read The Manual](http://zeromq.org/intro:read-the-manual)
    - [ ] [ActiveMQ](http://activemq.apache.org/)
    - [ ] [Kafka](http://kafka.apache.org/documentation.html#introduction)
    - [ ] [MessagePack](http://msgpack.org/index.html)
    - [ ] [Avro](https://avro.apache.org/)

- ### A*
    - [ ] [A Search Algorithm](https://en.wikipedia.org/wiki/A*_search_algorithm)
    - [ ] [A* Pathfinding Tutorial (video)](https://www.youtube.com/watch?v=KNXfSOx4eEE)
    - [ ] [A* Pathfinding (E01: algorithm explanation) (video)](https://www.youtube.com/watch?v=-L-WgKMFuhE)

- ### Fast Fourier Transform
    - [ ] [An Interactive Guide To The Fourier Transform](https://betterexplained.com/articles/an-interactive-guide-to-the-fourier-transform/)
    - [ ] [What is a Fourier transform? What is it used for?](http://www.askamathematician.com/2012/09/q-what-is-a-fourier-transform-what-is-it-used-for/)
    - [ ] [What is the Fourier Transform? (video)](https://www.youtube.com/watch?v=Xxut2PN-V8Q)
    - [ ] [Divide & Conquer: FFT (video)](https://www.youtube.com/watch?v=iTMn0Kt18tg&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=4)
    - [ ] [Understanding The FFT](http://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/)

- ### Bloom Filter
    - Given a Bloom filter with m bits and k hashing functions, both insertion and membership testing are O(k)
    - [Bloom Filters](https://www.youtube.com/watch?v=-SuTGoFYjZs)
    - [Bloom Filters | Mining of Massive Datasets | Stanford University](https://www.youtube.com/watch?v=qBTdukbzc78)
    - [Tutorial](http://billmill.org/bloomfilter-tutorial/)
    - [How To Write A Bloom Filter App](http://blog.michaelschmatz.com/2016/04/11/how-to-write-a-bloom-filter-cpp/)

- ### HyperLogLog
    - [How To Count A Billion Distinct Objects Using Only 1.5KB Of Memory](http://highscalability.com/blog/2012/4/5/big-data-counting-how-to-count-a-billion-distinct-objects-us.html)

- ### Locality-Sensitive Hashing
    - used to determine the similarity of documents
    - the opposite of MD5 or SHA which are used to determine if 2 documents/strings are exactly the same.
    - [Simhashing (hopefully) made simple](http://ferd.ca/simhashing-hopefully-made-simple.html)

- ### van Emde Boas Trees
    - [ ] [Divide & Conquer: van Emde Boas Trees (video)](https://www.youtube.com/watch?v=hmReJCupbNU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=6)
    - [ ] [MIT Lecture Notes](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms-spring-2012/lecture-notes/MIT6_046JS12_lec15.pdf)

- ### Augmented Data Structures
    - [ ] [CS 61B Lecture 39: Augmenting Data Structures](https://youtu.be/zksIj9O8_jc?list=PL4BBB74C7D2A1049C&t=950)

- ### Balanced search trees
    - Know least one type of balanced binary tree (and know how it's implemented):
    - "Among balanced search trees, AVL and 2/3 trees are now passé, and red-black trees seem to be more popular.
        A particularly interesting self-organizing data structure is the splay tree, which uses rotations
        to move any accessed key to the root." - Skiena
    - Of these, I chose to implement a splay tree. From what I've read, you won't implement a
        balanced search tree in your interview. But I wanted exposure to coding one up
        and let's face it, splay trees are the bee's knees. I did read a lot of red-black tree code.
        - splay tree: insert, search, delete functions
        If you end up implementing red/black tree try just these:
        - search and insertion functions, skipping delete
    - I want to learn more about B-Tree since it's used so widely with very large data sets.
    - [ ] [Self-balancing binary search tree](https://en.wikipedia.org/wiki/Self-balancing_binary_search_tree)

    - [ ] **AVL trees**
        - In practice:
            From what I can tell, these aren't used much in practice, but I could see where they would be:
            The AVL tree is another structure supporting O(log n) search, insertion, and removal. It is more rigidly
            balanced than red–black trees, leading to slower insertion and removal but faster retrieval. This makes it
            attractive for data structures that may be built once and loaded without reconstruction, such as language
            dictionaries (or program dictionaries, such as the opcodes of an assembler or interpreter).
        - [ ] [MIT AVL Trees / AVL Sort (video)](https://www.youtube.com/watch?v=FNeL18KsWPc&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=6)
        - [ ] [AVL Trees (video)](https://www.coursera.org/learn/data-structures/lecture/Qq5E0/avl-trees)
        - [ ] [AVL Tree Implementation (video)](https://www.coursera.org/learn/data-structures/lecture/PKEBC/avl-tree-implementation)
        - [ ] [Split And Merge](https://www.coursera.org/learn/data-structures/lecture/22BgE/split-and-merge)

    - [ ] **Splay trees**
        - In practice:
            Splay trees are typically used in the implementation of caches, memory allocators, routers, garbage collectors,
            data compression, ropes (replacement of string used for long text strings), in Windows NT (in the virtual memory,
            networking and file system code) etc.
        - [ ] [CS 61B: Splay Trees (video)](https://www.youtube.com/watch?v=Najzh1rYQTo&index=23&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)
        - [ ] MIT Lecture: Splay Trees:
            - Gets very mathy, but watch the last 10 minutes for sure.
            - [Video](https://www.youtube.com/watch?v=QnPl_Y6EqMo)

    - [ ] **Red/black trees**
        - these are a translation of a 2-3 tree (see below)
        - In practice:
            Red–black trees offer worst-case guarantees for insertion time, deletion time, and search time.
            Not only does this make them valuable in time-sensitive applications such as real-time applications,
            but it makes them valuable building blocks in other data structures which provide worst-case guarantees;
            for example, many data structures used in computational geometry can be based on red–black trees, and
            the Completely Fair Scheduler used in current Linux kernels uses red–black trees. In the version 8 of Java,
            the Collection HashMap has been modified such that instead of using a LinkedList to store identical elements with poor
            hashcodes, a Red-Black tree is used.
        - [ ] [Aduni - Algorithms - Lecture 4 (link jumps to starting point) (video)](https://youtu.be/1W3x0f_RmUo?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3871)
        - [ ] [Aduni - Algorithms - Lecture 5 (video)](https://www.youtube.com/watch?v=hm2GHwyKF1o&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=5)
        - [ ] [Black Tree](https://en.wikipedia.org/wiki/Red%E2%80%93black_tree)
        - [ ] [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/data-science/data-science-tutorials/an-introduction-to-binary-search-and-red-black-trees/)

    - [ ] **2-3 search trees**
        - In practice:
            2-3 trees have faster inserts at the expense of slower searches (since height is more compared to AVL trees).
        - You would use 2-3 tree very rarely because its implementation involves different types of nodes. Instead, people use Red Black trees.
        - [ ] [23-Tree Intuition and Definition (video)](https://www.youtube.com/watch?v=C3SsdUqasD4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=2)
        - [ ] [Binary View of 23-Tree](https://www.youtube.com/watch?v=iYvBtGKsqSg&index=3&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [2-3 Trees (student recitation) (video)](https://www.youtube.com/watch?v=TOb1tuEZ2X4&index=5&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

    - [ ] **2-3-4 Trees (aka 2-4 trees)**
        - In practice:
            For every 2-4 tree, there are corresponding red–black trees with data elements in the same order. The insertion and deletion
            operations on 2-4 trees are also equivalent to color-flipping and rotations in red–black trees. This makes 2-4 trees an
            important tool for understanding the logic behind red–black trees, and this is why many introductory algorithm texts introduce
            2-4 trees just before red–black trees, even though **2-4 trees are not often used in practice**.
        - [ ] [CS 61B Lecture 26: Balanced Search Trees (video)](https://www.youtube.com/watch?v=zqrqYXkth6Q&index=26&list=PL4BBB74C7D2A1049C)
        - [ ] [Bottom Up 234-Trees (video)](https://www.youtube.com/watch?v=DQdMYevEyE4&index=4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [Top Down 234-Trees (video)](https://www.youtube.com/watch?v=2679VQ26Fp4&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=5)

    - [ ] **N-ary (K-ary, M-ary) trees**
        - note: the N or K is the branching factor (max branches)
        - binary trees are a 2-ary tree, with branching factor = 2
        - 2-3 trees are 3-ary
        - [ ] [K-Ary Tree](https://en.wikipedia.org/wiki/K-ary_tree)

    - [ ] **B-Trees**
        - fun fact: it's a mystery, but the B could stand for Boeing, Balanced, or Bayer (co-inventor)
        - In Practice:
            B-Trees are widely used in databases. Most modern filesystems use B-trees (or Variants). In addition to
            its use in databases, the B-tree is also used in filesystems to allow quick random access to an arbitrary
            block in a particular file. The basic problem is turning the file block i address into a disk block
            (or perhaps to a cylinder-head-sector) address.
        - [ ] [B-Tree](https://en.wikipedia.org/wiki/B-tree)
        - [ ] [Introduction to B-Trees (video)](https://www.youtube.com/watch?v=I22wEC1tTGo&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6&index=6)
        - [ ] [B-Tree Definition and Insertion (video)](https://www.youtube.com/watch?v=s3bCdZGrgpA&index=7&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [B-Tree Deletion (video)](https://www.youtube.com/watch?v=svfnVhJOfMc&index=8&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
        - [ ] [MIT 6.851 - Memory Hierarchy Models (video)](https://www.youtube.com/watch?v=V3omVLzI0WE&index=7&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf)
                - covers cache-oblivious B-Trees, very interesting data structures
                - the first 37 minutes are very technical, may be skipped (B is block size, cache line size)


- ### k-D Trees
    - great for finding number of points in a rectangle or higher dimension object
    - a good fit for k-nearest neighbors
    - [ ] [Kd Trees (video)](https://www.youtube.com/watch?v=W94M9D_yXKk)
    - [ ] [kNN K-d tree algorithm (video)](https://www.youtube.com/watch?v=Y4ZgLlDfKDg)

- ### Skip lists
    - "These are somewhat of a cult data structure" - Skiena
    - [ ] [Randomization: Skip Lists (video)](https://www.youtube.com/watch?v=2g9OSRKJuzM&index=10&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [For animations and a little more detail](https://en.wikipedia.org/wiki/Skip_list)

- ### Network Flows
    - [ ] [Ford-Fulkerson in 5 minutes (video)](https://www.youtube.com/watch?v=v1VgJmkEJW0)
    - [ ] [Ford-Fulkerson Algorithm (video)](https://www.youtube.com/watch?v=v1VgJmkEJW0)
    - [ ] [Network Flows (video)](https://www.youtube.com/watch?v=2vhN4Ice5jI)

- ### Disjoint Sets & Union Find
    - [ ] [UCB 61B - Disjoint Sets; Sorting & selection (video)](https://www.youtube.com/watch?v=MAEGXTwmUsI&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=21)
    - [ ] [Sedgewick Algorithms - Union-Find (6 videos)](https://www.youtube.com/watch?v=8mYfZeHtdNc&list=PLe-ggMe31CTexoNYnMhbHaWhQ0dvcy43t)

- ### Math for Fast Processing
    - [ ] [Integer Arithmetic, Karatsuba Multiplication (video)](https://www.youtube.com/watch?v=eCaXlAaN2uE&index=11&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [The Chinese Remainder Theorem (used in cryptography) (video)](https://www.youtube.com/watch?v=ru7mWZJlRQg)

- ### Treap
    - Combination of a binary search tree and a heap
    - [ ] [Treap](https://en.wikipedia.org/wiki/Treap)
    - [ ] [Data Structures: Treaps explained (video)](https://www.youtube.com/watch?v=6podLUYinH8)
    - [ ] [Applications in set operations](https://www.cs.cmu.edu/~scandal/papers/treaps-spaa98.pdf)

- ### Linear Programming (videos)
    - [ ] [Linear Programming](https://www.youtube.com/watch?v=M4K6HYLHREQ)
    - [ ] [Finding minimum cost](https://www.youtube.com/watch?v=2ACJ9ewUC6U)
    - [ ] [Finding maximum value](https://www.youtube.com/watch?v=8AA_81xI3ik)
    - [ ] [Solve Linear Equations with Python - Simplex Algorithm](https://www.youtube.com/watch?v=44pAWI7v5Zk)

- ### Geometry, Convex hull (videos)
    - [ ] [Graph Alg. IV: Intro to geometric algorithms - Lecture 9](https://youtu.be/XIAQRlNkJAw?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3164)
    - [ ] [Geometric Algorithms: Graham & Jarvis - Lecture 10](https://www.youtube.com/watch?v=J5aJEcOr6Eo&index=10&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm)
    - [ ] [Divide & Conquer: Convex Hull, Median Finding](https://www.youtube.com/watch?v=EzeYI7p9MjU&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=2)

- ### Discrete math
    - see videos below

- ### Machine Learning
    - [ ] Why ML?
        - [ ] [How Google Is Remaking Itself As A Machine Learning First Company](https://backchannel.com/how-google-is-remaking-itself-as-a-machine-learning-first-company-ada63defcb70)
        - [ ] [Large-Scale Deep Learning for Intelligent Computer Systems (video)](https://www.youtube.com/watch?v=QSaZGT4-6EY)
        - [ ] [Deep Learning and Understandability versus Software Engineering and Verification by Peter Norvig](https://www.youtube.com/watch?v=X769cyzBNVw)
    - [ ] [Google's Cloud Machine learning tools (video)](https://www.youtube.com/watch?v=Ja2hxBAwG_0)
    - [ ] [Google Developers' Machine Learning Recipes (Scikit Learn & Tensorflow) (video)](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal)
    - [ ] [Tensorflow (video)](https://www.youtube.com/watch?v=oZikw5k_2FM)
    - [ ] [Tensorflow Tutorials](https://www.tensorflow.org/versions/r0.11/tutorials/index.html)
    - [ ] [Practical Guide to implementing Neural Networks in Python (using Theano)](http://www.analyticsvidhya.com/blog/2016/04/neural-networks-python-theano/)
    - Courses:
        - [Great starter course: Machine Learning](https://www.coursera.org/learn/machine-learning)
              - [videos only](https://www.youtube.com/playlist?list=PLZ9qNFMHZ-A4rycgrgOYma6zxF4BZGGPW)
              - see videos 12-18 for a review of linear algebra (14 and 15 are duplicates)
        - [Neural Networks for Machine Learning](https://www.coursera.org/learn/neural-networks)
        - [Google's Deep Learning Nanodegree](https://www.udacity.com/course/deep-learning--ud730)
        - [Google/Kaggle Machine Learning Engineer Nanodegree](https://www.udacity.com/course/machine-learning-engineer-nanodegree-by-google--nd009)
        - [Self-Driving Car Engineer Nanodegree](https://www.udacity.com/drive)
        - [Metis Online Course ($99 for 2 months)](http://www.thisismetis.com/explore-data-science)
    - Resources:
        - Books:
            - [Python Machine Learning](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/)
            - [Data Science from Scratch: First Principles with Python](https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X)
            - [Introduction to Machine Learning with Python](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/)
        - [Machine Learning for Software Engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)
        - Data School: http://www.dataschool.io/

--

## Additional Detail on Some Subjects

    I added these to reinforce some ideas already presented above, but didn't want to include them
    above because it's just too much. It's easy to overdo it on a subject.
    You want to get hired in this century, right?

- [ ] **Union-Find**
    - [ ] [Overview](https://www.coursera.org/learn/data-structures/lecture/JssSY/overview)
    - [ ] [Naive Implementation](https://www.coursera.org/learn/data-structures/lecture/EM5D0/naive-implementations)
    - [ ] [Trees](https://www.coursera.org/learn/data-structures/lecture/Mxu0w/trees)
    - [ ] [Union By Rank](https://www.coursera.org/learn/data-structures/lecture/qb4c2/union-by-rank)
    - [ ] [Path Compression](https://www.coursera.org/learn/data-structures/lecture/Q9CVI/path-compression)
    - [ ] [Analysis Options](https://www.coursera.org/learn/data-structures/lecture/GQQLN/analysis-optional)

- [ ] **More Dynamic Programming** (videos)
    - [ ] [6.006: Dynamic Programming I: Fibonacci, Shortest Paths](https://www.youtube.com/watch?v=OQ5jsbhAv_M&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=19)
    - [ ] [6.006: Dynamic Programming II: Text Justification, Blackjack](https://www.youtube.com/watch?v=ENyox7kNKeY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=20)
    - [ ] [6.006: DP III: Parenthesization, Edit Distance, Knapsack](https://www.youtube.com/watch?v=ocZMDMZwhCY&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=21)
    - [ ] [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [6.046: Dynamic Programming & Advanced DP](https://www.youtube.com/watch?v=Tw1k46ywN6E&index=14&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)
    - [ ] [6.046: Dynamic Programming: All-Pairs Shortest Paths](https://www.youtube.com/watch?v=NzgFUwOaoIw&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=15)
    - [ ] [6.046: Dynamic Programming (student recitation)](https://www.youtube.com/watch?v=krZI60lKPek&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=12)

- [ ] **Advanced Graph Processing** (videos)
    - [ ] [Synchronous Distributed Algorithms: Symmetry-Breaking. Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=mUBmcbbJNf4&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=27)
    - [ ] [Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees](https://www.youtube.com/watch?v=kQ-UQAzcnzA&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=28)

- [ ] MIT **Probability** (mathy, and go slowly, which is good for mathy things) (videos):
    - [ ] [MIT 6.042J - Probability Introduction](https://www.youtube.com/watch?v=SmFwFdESMHI&index=18&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Conditional Probability](https://www.youtube.com/watch?v=E6FbvM-FGZ8&index=19&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Independence](https://www.youtube.com/watch?v=l1BCv3qqW4A&index=20&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Random Variables](https://www.youtube.com/watch?v=MOfhhFaQdjw&list=PLB7540DEDD482705B&index=21)
    - [ ] [MIT 6.042J - Expectation I](https://www.youtube.com/watch?v=gGlMSe7uEkA&index=22&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Expectation II](https://www.youtube.com/watch?v=oI9fMUqgfxY&index=23&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Large Deviations](https://www.youtube.com/watch?v=q4mwO2qS2z4&index=24&list=PLB7540DEDD482705B)
    - [ ] [MIT 6.042J - Random Walks](https://www.youtube.com/watch?v=56iFMY8QW2k&list=PLB7540DEDD482705B&index=25)

- [ ] [Simonson: Approximation Algorithms (video)](https://www.youtube.com/watch?v=oDniZCmNmNw&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=19)

- [ ] **String Matching**
    - [ ] Rabin-Karp (videos):
        - [Rabin Karps Algorithm](https://www.coursera.org/learn/data-structures/lecture/c0Qkw/rabin-karps-algorithm)
        - [Precomputing](https://www.coursera.org/learn/data-structures/lecture/nYrc8/optimization-precomputation)
        - [Optimization: Implementation and Analysis](https://www.coursera.org/learn/data-structures/lecture/h4ZLc/optimization-implementation-and-analysis)
        - [Table Doubling, Karp-Rabin](https://www.youtube.com/watch?v=BRO7mVIFt08&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=9)
        - [Rolling Hashes, Amortized Analysis](https://www.youtube.com/watch?v=w6nuXg0BISo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=32)
    - [ ] Knuth-Morris-Pratt (KMP):
        - [TThe Knuth-Morris-Pratt (KMP) String Matching Algorithm](https://www.youtube.com/watch?v=5i7oKodCRJo)
    - [ ] Boyer–Moore string search algorithm
        - [Boyer-Moore String Search Algorithm](https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore_string_search_algorithm)
        - [Advanced String Searching Boyer-Moore-Horspool Algorithms (video)](https://www.youtube.com/watch?v=QDZpzctPf10)
    - [ ] [Coursera: Algorithms on Strings](https://www.coursera.org/learn/algorithms-on-strings/home/week/1)
        - starts off great, but by the time it gets past KMP it gets more complicated than it needs to be
        - nice explanation of tries
        - can be skipped

- [ ] **Sorting**

    - [ ] Stanford lectures on sorting:
        - [ ] [Lecture 15 | Programming Abstractions (video)](https://www.youtube.com/watch?v=ENp00xylP7c&index=15&list=PLFE6E58F856038C69)
        - [ ] [Lecture 16 | Programming Abstractions (video)](https://www.youtube.com/watch?v=y4M9IVgrVKo&index=16&list=PLFE6E58F856038C69)
    - [ ] Shai Simonson, [Aduni.org](http://www.aduni.org/):
        - [ ] [Algorithms - Sorting - Lecture 2 (video)](https://www.youtube.com/watch?v=odNJmw5TOEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=2)
        - [ ] [Algorithms - Sorting II - Lecture 3 (video)](https://www.youtube.com/watch?v=hj8YKFTFKEE&list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&index=3)
    - [ ] Steven Skiena lectures on sorting:
        - [ ] [lecture begins at 26:46 (video)](https://youtu.be/ute-pmMkyuk?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&t=1600)
        - [ ] [lecture begins at 27:40 (video)](https://www.youtube.com/watch?v=yLvp-pB8mak&index=8&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
        - [ ] [lecture begins at 35:00 (video)](https://www.youtube.com/watch?v=q7K9otnzlfE&index=9&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b)
        - [ ] [lecture begins at 23:50 (video)](https://www.youtube.com/watch?v=TvqIGu9Iupw&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=10)

## Video Series

Sit back and enjoy. "Netflix and skill" :P

- [ ] [List of individual Dynamic Programming problems (each is short)](https://www.youtube.com/playlist?list=PLrmLmBdmIlpsHaNTPP_jHHDx_os9ItYXr)

- [ ] [x86 Architecture, Assembly, Applications (11 videos)](https://www.youtube.com/playlist?list=PL038BE01D3BAEFDB0)

- [ ] [MIT 18.06 Linear Algebra, Spring 2005 (35 videos)](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8)

- [ ] [Excellent - MIT Calculus Revisited: Single Variable Calculus](https://www.youtube.com/playlist?list=PL3B08AE665AB9002A)

- [ ] [Computer Science 70, 001 - Spring 2015 - Discrete Mathematics and Probability Theory](https://www.youtube.com/playlist?list=PL-XXv-cvA_iD8wQm8U0gG_Z1uHjImKXFy)

- [ ] [Discrete Mathematics by Shai Simonson (19 videos)](https://www.youtube.com/playlist?list=PL3o9D4Dl2FJ9q0_gtFXPh_H4POI5dK0yG)

- [ ] [Discrete Mathematics Part 1 by Sarada Herke (5 videos)](https://www.youtube.com/playlist?list=PLGxuz-nmYlQPOc4w1Kp2MZrdqOOm4Jxeo)

- [ ] CSE373 - Analysis of Algorithms (25 videos)
    - [Skiena lectures from Algorithm Design Manual](https://www.youtube.com/watch?v=ZFjhkohHdAA&list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b&index=1)

- [ ] [UC Berkeley 61B (Spring 2014): Data Structures (25 videos)](https://www.youtube.com/watch?v=mFPmKGIrQs4&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)

- [ ] [UC Berkeley 61B (Fall 2006): Data Structures (39 videos)](https://www.youtube.com/playlist?list=PL4BBB74C7D2A1049C)

- [ ] [UC Berkeley 61C: Machine Structures (26 videos)](https://www.youtube.com/watch?v=gJJeUFyuvvg&list=PL-XXv-cvA_iCl2-D-FS5mk0jFF6cYSJs_)

- [ ] [OOSE: Software Dev Using UML and Java (21 videos)](https://www.youtube.com/playlist?list=PLJ9pm_Rc9HesnkwKlal_buSIHA-jTZMpO)

- [ ] [UC Berkeley CS 152: Computer Architecture and Engineering (20 videos)](https://www.youtube.com/watch?v=UH0QYvtP7Rk&index=20&list=PLkFD6_40KJIwEiwQx1dACXwh-2Fuo32qr)

- [ ] [MIT 6.004: Computation Structures (49 videos)](https://www.youtube.com/playlist?list=PLrRW1w6CGAcXbMtDFj205vALOGmiRc82-)

- [ ] [Carnegie Mellon - Computer Architecture Lectures (39 videos)](https://www.youtube.com/playlist?list=PL5PHm2jkkXmi5CxxI7b3JCL1TWybTDtKq)

- [ ] [MIT 6.006: Intro to Algorithms (47 videos)](https://www.youtube.com/watch?v=HtSuA80QTyo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&nohtml5=False)

- [ ] [MIT 6.033: Computer System Engineering (22 videos)](https://www.youtube.com/watch?v=zm2VP0kHl1M&list=PL6535748F59DCA484)

- [ ] [MIT 6.034 Artificial Intelligence, Fall 2010 (30 videos)](https://www.youtube.com/playlist?list=PLUl4u3cNGP63gFHB6xb-kVBiQHYe_4hSi)

- [ ] [MIT 6.042J: Mathematics for Computer Science, Fall 2010 (25 videos)](https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B)

- [ ] [MIT 6.046: Design and Analysis of Algorithms (34 videos)](https://www.youtube.com/watch?v=2P-yW7LQr08&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp)

- [ ] [MIT 6.050J: Information and Entropy, Spring 2008 (19 videos)](https://www.youtube.com/watch?v=phxsQrZQupo&list=PL_2Bwul6T-A7OldmhGODImZL8KEVE38X7)

- [ ] [MIT 6.851: Advanced Data Structures (22 videos)](https://www.youtube.com/watch?v=T0yzrZL1py0&list=PLUl4u3cNGP61hsJNdULdudlRL493b-XZf&index=1)

- [ ] [MIT 6.854: Advanced Algorithms, Spring 2016 (24 videos)](https://www.youtube.com/playlist?list=PL6ogFv-ieghdoGKGg2Bik3Gl1glBTEu8c)

- [ ] [Harvard COMPSCI 224: Advanced Algorithms (25 videos)](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf)

- [ ] [MIT 6.858 Computer Systems Security, Fall 2014](https://www.youtube.com/watch?v=GqmQg-cszw4&index=1&list=PLUl4u3cNGP62K2DjQLRxDNRi0z2IRWnNh)

- [ ] [Stanford: Programming Paradigms (27 videos)](https://www.youtube.com/view_play_list?p=9D558D49CA734A02)

- [ ] [Introduction to Cryptography by Christof Paar](https://www.youtube.com/playlist?list=PL6N5qY2nvvJE8X75VkXglSrVhLv1tVcfy)
    - [Course Website along with Slides and Problem Sets](http://www.crypto-textbook.com/)

- [ ] [Mining Massive Datasets - Stanford University (94 videos)](https://www.youtube.com/playlist?list=PLLssT5z_DsK9JDLcT8T62VtzwyW9LNepV)

- [ ] [Graph Theory by Sarada Herke (67 videos)](https://www.youtube.com/user/DrSaradaHerke/playlists?shelf_id=5&view=50&sort=dd)

## Computer Science Courses

- [Directory of Online CS Courses](https://github.com/open-source-society/computer-science)
- [Directory of CS Courses (many with online lectures)](https://github.com/prakhar1989/awesome-courses)