> Przez kilka miesięcy uczyłem się około 8-12 godzin dziennie. Oto moja historia: [Dlaczego uczyłem się w pełnym wymiarze godzin przez 8 miesięcy na rozmowę w Google](https://medium.freecodecamp.org/why-i-studied-full-time-for-8-months-for-a-google-interview-cc662ce9bb13)
> Pozycje wymienione tutaj dobrze przygotują cię na wywiad techniczny w prawie każdej firmie zajmującej się wytwarzaniem oprogramowania, włączając w to takich gigantów jak: Amazon, Facebook, Google, and Microsoft.
To jest mój wielomiesięczny plan nauki od przejścia od programisty (samouka, bez dyplomu CS - informatyki) do inżyniera oprogramowania dla dużej firmy.
Jest to przeznaczone dla **początkujących software engineers** lub tych przełączających się z software/web development na software engineering (gdzie wiedza z informatyki jest wymagana). Jeśli masz wieloletnie doświadczenie i stwierdziłeś, że masz wieloletnie doświadczenie w inżynierii oprogramowania, oczekuj trudniejszej rozmowy.
Jeśli masz wieloletnie doświadczenie w tworzeniu oprogramowania/stron internetowych, pamiętaj, że duże firmy programistyczne, takie jak Google, Amazon, Facebook i Microsoft postrzegają inżynierię oprogramowania jako inną niż tworzenie oprogramowania / stron internetowych i wymagają wiedzy informatycznej.
Kiedy rozpocząłem ten projekt, nie rozpoznawałem stosu (stack) od sterty (heap), nie znałem notacji dużego O (złożoności obliczeniowej algorytmów, asymptotycznego tempa wzrostu), nie wiedziałem nic o drzewach ani tego, jak przejść przez graf. Gdybym musiał kodować algorytm sortowania, mogę powiedzieć, że nie byłby zbyt dobry.
Wszystkie struktury danych, z którymi miałem kiedykolwiek do czynienia, były wbudowane w język i nie wiedziałem w ogóle, jak działają pod maską. Nigdy nie musiałem zarządzać pamięcią, chyba że uruchamiany przeze mnie proces wyrzuciłby błąd "out of
memory", a potem musiałbym znaleźć obejście. W swoim życiu użyłem kilku wielowymiarowych tablic i tysiące tablic asocjacyjnych, ale nigdy nie tworzyłem struktur danych od zera.
Będę wdzięczny za pomoc w dodawaniu bezpłatnych i zawsze dostępnych źródeł publicznych, takich jak filmy z YouTube, które towarzyszą filmom z kursów online.
- [ ] [Python for Data Structures, Algorithms, and Interviews (paid course)](https://www.udemy.com/python-for-data-structures-algorithms-and-interviews/):
- [ ] [Intro to Data Structures and Algorithms using Python (Udacity free course)](https://www.udacity.com/course/data-structures-and-algorithms-in-python--ud513):
- Przećwicz praktyczne ćwiczenia z ponad 100 struktur danych i ćwiczeń algorytmicznych oraz wskazówek od dedykowanego mentora, aby pomóc Ci przygotować się na rozmowy kwalifikacyjne i scenariusze w miejscu pracy.
Możesz użyć języka, w którym czujesz się komfortowo, aby wykonać część wywiadu dotyczącą programowania, ale w przypadku dużych firm są to solidne propozycje:
Oto artykuł, który napisałem o wyborze języka do rozmowy kwalifikacyjnej: [Wybierz jeden język do wywiadu kodującego](https://startupnextdoor.com/important-pick-one-language-for-the-coding-interview/)
- [ ] [Programming Interviews Exposed: Coding Your Way Through the Interview, 4th Edition](https://www.amazon.com/Programming-Interviews-Exposed-Through-Interview/dp/111941847X/)
Jeśli zapoznasz się z jednym z nich, powinieneś mieć całą wiedzę na temat struktur danych i algorytmów, których potrzebujesz, aby zacząć robić problemy z kodowaniem.
**Możesz pominąć wszystkie wykłady wideo w tym projekcie**, chyba że chcesz recenzję.
- [ ] [Algorithms in C++, Parts 1-4: Fundamentals, Data Structure, Sorting, Searching](https://www.amazon.com/Algorithms-Parts-1-4-Fundamentals-Structure/dp/0201350882/)
- [ ] [Algorithms in C++ Part 5: Graph Algorithms](https://www.amazon.com/Algorithms-Part-Graph-3rd-Pt-5/dp/0201361183/)
Pamiętaj, że poszedłem ostro i mam karty obejmujące wszystko, od języka asemblera i ciekawostek Python po uczenie maszynowe i statystyki. To o wiele za dużo na to, w stosunku do tego co jest wymagane.
Alternatywą dla korzystania z mojej strony z kartami jest [Anki](http://ankisrs.net/), która była mi polecana wiele razy. Używa systemu powtarzania, aby pomóc Ci zapamiętać.
Jest przyjazna dla użytkownika, dostępna na wszystkich platformach i ma system synchronizacji w chmurze. Kosztuje $25 na iOS ale jest darmowa na innych platformach.
Musisz zastosować zdobytą wiedzę do rozwiązywania problemów, inaczej zapomnisz. Popełniłem ten błąd. Gdy nauczysz się tematu,
aby czuć się z tym komfortowo, np. listy powiązane - otwórz jedną z książek o rekrutacji IT i zrób kilka pytań dotyczących list powiązanych (linked lists). Następnie przejdź do następnego tematu do nauki. Potem wróć i zrób kolejne zadanie z listą powiązaną, problem z rekurencją lub cokolwiek innego. Ale rób zadania podczas nauki. Nie jesteś zatrudniony do wiedzy,
ale do tego jak zastosować wiedzę. Polecam kilka książek i stron.
Zobacz tutaj, aby uzyskać więcej informacji: [Praktyczne pytania programistyczne](#coding-question-practice)
I keep a set of cheat sheets on ASCII, OSI stack, Big-O notations, and more. I study them when I have some spare time.
Take a break from programming problems for a half hour and go through your flashcards.
### 5. Focus
There are a lot of distractions that can take up valuable time. Focus and concentration are hard. Turn on some music
without lyrics and you'll be able to focus pretty well.
## What you won't see covered
These are prevalent technologies but not part of this study plan:
- SQL
- Javascript
- HTML, CSS, and other front-end technologies
## 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 or Java))
- 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.
- [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU)
- [ ] [Big O Notation (and Omega and Theta) - best mathematical explanation (video)](https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- not the whole video, just portions about Node struct and memory allocation.
- [ ] Linked List vs Arrays:
- [Core Linked Lists Vs Arrays (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/rjBs9/core-linked-lists-vs-arrays)
- [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)
- [ ] [why you should avoid linked lists (video)](https://www.youtube.com/watch?v=YQs6IC-vgmo)
- [ ] Gotcha: you need pointer to pointer knowledge:
(for when you pass a pointer to a function that may change the address where that pointer points)
This page is just to get a grasp on ptr to ptr. I don't recommend this list traversal style. Readability and maintainability suffer due to cleverness.
- [Pointers to Pointers](https://www.eskimo.com/~scs/cclass/int/sx8.html)
- [ ] implement (I did with tail pointer & without):
- [ ] size() - returns number of data elements in list
- [ ] empty() - bool returns true if empty
- [ ] value_at(index) - returns the value of the nth item (starting at 0 for first)
- [ ] push_front(value) - adds an item to the front of the list
- [ ] pop_front() - remove front item and return its value
- [ ] push_back(value) - adds an item at the end
- [ ] pop_back() - removes end item and returns its value
- [ ] front() - get value of front item
- [ ] back() - get value of end item
- [ ] insert(index, value) - insert value at index, so current item at that index is pointed to by new item at index
- [ ] erase(index) - removes node at given index
- [ ] value_n_from_end(n) - returns the value of the node at nth position from the end of the list
- [ ] reverse() - reverses the list
- [ ] remove_value(value) - removes the first item in the list with this value
- [ ] [Phone Book Problem (video)](https://www.coursera.org/learn/data-structures/lecture/NYZZP/phone-book-problem)
- [ ] distributed hash tables:
- [Instant Uploads And Storage Optimization In Dropbox (video)](https://www.coursera.org/learn/data-structures/lecture/DvaIb/instant-uploads-and-storage-optimization-in-dropbox)
- [ ] [Bits cheat sheet](https://github.com/jwasham/coding-interview-university/blob/master/extras/cheat%20sheets/bits-cheat-cheet.pdf) - you should know many of the powers of 2 from (2^1 to 2^16 and 2^32)
- [ ] Get a really good understanding of manipulating bits with: &, |, ^, ~, >>, <<
- [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)
- [ ] [Binary search tree - Implementation in C/C++ (video)](https://www.youtube.com/watch?v=COZK7NATh4k&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=28)
- [ ] [BST implementation - memory allocation in stack and heap (video)](https://www.youtube.com/watch?v=hWokyBoo0aI&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=29)
- [ ] [Find min and max element in a binary search tree (video)](https://www.youtube.com/watch?v=Ut90klNN264&index=30&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Find height of a binary tree (video)](https://www.youtube.com/watch?v=_pnqMz5nrRs&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=31)
- [ ] [Binary tree traversal - breadth-first and depth-first strategies (video)](https://www.youtube.com/watch?v=9RHO6jU--GU&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=32)
- [ ] [Binary tree: Level Order Traversal (video)](https://www.youtube.com/watch?v=86g8jAQug04&index=33&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [Binary tree traversal: Preorder, Inorder, Postorder (video)](https://www.youtube.com/watch?v=gm8DUJJhmY4&index=34&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] [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)
- [ ] [Delete a node from Binary Search Tree (video)](https://www.youtube.com/watch?v=gcULXE7ViZw&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&index=36)
- [ ] [Inorder Successor in a binary search tree (video)](https://www.youtube.com/watch?v=5cPbNCrdotA&index=37&list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P)
- [ ] Implement:
- [ ] insert // insert value into tree
- [ ] get_node_count // get count of values stored
- [ ] print_values // prints the values in the tree, from min to max
- [ ] delete_tree
- [ ] is_in_tree // returns true if given value exists in the tree
- [ ] get_height // returns the height in nodes (single node's height is 1)
- [ ] get_min // returns the minimum value stored in the tree
- [ ] get_max // returns the maximum value stored in the tree
- [ ] is_binary_search_tree
- [ ] delete_value
- [ ] get_successor // returns next-highest value in tree after given value, -1 if none
- ### Heap / Priority Queue / Binary Heap
- visualized as a tree, but is usually linear in storage (array, linked list)
- You probably won't see any dynamic programming problems in your interview, but it's worth being able to recognize a problem as being a candidate for 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.
- [ ] Videos:
- the Skiena videos can be hard to follow since he sometimes uses the whiteboard, which is too small to see
- 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)
- [ ] [3. Character Based Operations](https://www.coursera.org/learn/algorithms-part2/lecture/jwNmV/character-based-operations)
- [ ] [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/competitive-programming/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) (video)](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)
- [ ] [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://web.archive.org/web/20180107141940/http://www.cs.umd.edu:80/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 reliability engineer or operations engineer, expect questions**
**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**: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
- [ ] [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/)
- [ ] [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/)
- [ ] [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)
- [ ] [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)
- [ ] [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)
- [ ] [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)
- [ ] [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)
- [ ] [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](#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: [The System Design Primer](https://github.com/donnemartin/system-design-primer)
- [System Design from HiredInTech](http://www.hiredintech.com/system-design/)
- [Mathematics for Topcoders](https://www.topcoder.com/community/competitive-programming/tutorials/mathematics-for-topcoders/)
- [Dynamic Programming – From Novice to Advanced](https://www.topcoder.com/community/competitive-programming/tutorials/dynamic-programming-from-novice-to-advanced/)
- [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/competitive-programming/tutorials/how-to-find-a-solution/)
- [How to Dissect a Topcoder Problem Statement](https://www.topcoder.com/community/competitive-programming/tutorials/how-to-dissect-a-topcoder-problem-statement/)
- [Interactive Coding Interview Challenges in Python](https://github.com/donnemartin/interactive-coding-challenges)
Mock Interviews:
- [Gainlo.co: Mock interviewers from big companies](http://www.gainlo.co/) - I used this and it helped me relax for the phone screen and on-site interview.
- [Pramp: Mock interviews from/with peers](https://www.pramp.com/) - peer-to-peer model of practice interviews
- [Refdash: Mock interviews and expedited interviews](https://refdash.com/) - also help candidates fast track by skipping multiple interviews with tech companies.
## 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)
## 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?
- [Head First Design Patterns](https://www.amazon.com/gp/product/0596007124/)
- a gentle introduction to design patterns
- [Design Patterns: Elements of Reusable Object-Oriented 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, 5th Edition](https://www.amazon.com/UNIX-Linux-System-Administration-Handbook/dp/0134277554/)
- [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038)
- The book was published in 2004, and is somewhat outdated, but it's a terrific resource for understanding a computer in brief.
- The author invented [HLA](https://en.wikipedia.org/wiki/High_Level_Assembly), so take mentions and examples in HLA with a grain of salt. Not widely used, but decent examples of what assembly looks like.
- These chapters are worth the read to give you a nice foundation:
- Chapter 2 - Numeric Representation
- 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
- [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-3rd-MIT-Press/dp/0262033844)
- **Important:** Reading this book will only have limited value. This book is a great review of algorithms and data structures, but won't teach you how to write good code. You have to be able to code a decent solution efficiently.
- aka CLR, sometimes CLRS, because Stein was late to the game
- [Computer Architecture, Sixth Edition: A Quantitative Approach](https://www.amazon.com/dp/0128119055)
- For a richer, more up-to-date (2017), but longer treatment
- 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)
- [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.
- [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)
- [An Introduction To Binary Search And Red Black Tree](https://www.topcoder.com/community/competitive-programming/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://archive.org/details/ucberkeley_webcast_zqrqYXkth6Q)
- [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
- [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)
- [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?
- **SOLID**
- [ ] [Bob Martin SOLID Principles of Object Oriented and Agile Design (video)](https://www.youtube.com/watch?v=TMuno5RZNeE)
- [ ] 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)
- [ ] O - [Open/Closed Principal](http://www.oodesign.com/open-close-principle.html) | [On production level Objects are ready for extension but not for modification](https://en.wikipedia.org/wiki/Open/closed_principle)
- [ ] 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)
- [ ] 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)
- [ ] 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)
- [6.006: DP IV: Guitar Fingering, Tetris, Super Mario Bros.](https://www.youtube.com/watch?v=tp4_UXaVyx8&index=22&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
- [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](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs70-spring2015-berkeley.html)
- [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://archive.org/details/ucberkeley-webcast-PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd)
- [UC Berkeley 61B (Fall 2006): Data Structures (39 videos)](https://archive.org/details/ucberkeley-webcast-PL4BBB74C7D2A1049C)
- [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](http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.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)](https://www.akkadia.org/drepper/cpumemory.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)
- [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)