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Keonil Kim
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## Table of Contents
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- [구글 인터뷰 대학이란?](#what-is-it)
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- [구글 인터뷰 대학이란?](#구글-인터뷰-대학이란)
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- [Why use it?](#why-use-it)
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- [How to use it?](#how-to-use-it)
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- [구글 분위기 내기](#get-in-a-googley-mood)
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- [구글 분위기 내기](#구글-분위기-내기)
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- [Did I Get the Job](#did-i-get-the-job)
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- [팔로우 하려면](#follow-along-with-me)
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- [당신은 멍청하지 않다](#dont-feel-you-arent-smart-enough)
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- [구글에 대하여](#about-google)
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- [영상자료에 관하여](#about-video-resources)
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- [인터뷰 과정 & 일반적인 인터뷰 준비](#interview-process--general-interview-prep)
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- [인터뷰를 위한 언어 정하기](#pick-one-language-for-the-interview)
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- [도서 목록](#book-list)
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- [시작하기 전에](#before-you-get-started)
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- [목록에 없는 내용](#what-you-wont-see-covered)
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- [사전 지식](#prerequisite-knowledge)
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- [일일 계획](#the-daily-plan)
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- [알고리즘 복잡도 / Big-O / 점근적 분석](#algorithmic-complexity--big-o--asymptotic-analysis)
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- [자료구조](#data-structures)
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- [배열](#arrays)
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- [링크드 리스트](#linked-lists)
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- [스택](#stack)
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- [큐](#queue)
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- [해쉬 테이블](#hash-table)
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- [팔로우 하려면](#팔로우-하려면)
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- [당신은 충분히 똑똑합니다](#당신은-충분히-똑똑합니다)
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- [구글에 대해](#구글에-대해)
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- [영상 자료에 관하여](#영상-자료에-관하여)
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- [인터뷰 과정 & 전반적인 인터뷰 준비 과정](#인터뷰-과정--전반적인-인터뷰-준비-과정)
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- [인터뷰를 위한 언어 고르기](#인터뷰를-위한-언어-고르기)
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- [도서 목록](#도서-목록)
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- [시작하기 전에](#시작하기-전에)
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- [다루지 않을 것](#다루지-않을 것)
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- [선수 과목](#선수-과목)
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- [하루 하루의 계획](#하루-하루의-계획)
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- [알고리즘 복잡도 / Big-O / 점근적 분석](#알고리즘-복잡도--Big-O--점근적-분석)
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- [자료구조](#자료구조)
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- [배열](#배열)
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- [링크드 리스트](#링크드-리스트)
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- [스택](#스택)
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- [큐](#큐)
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- [해쉬 테이블](#해쉬-테이블)
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- [추가 지식](#more-knowledge)
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- [이진 검색](#binary-search)
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- [비트 연산](#bitwise-operations)
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@ -578,7 +578,7 @@ My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (
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- [ ] [How does CPU execute program (video)](https://www.youtube.com/watch?v=42KTvGYQYnA)
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- [ ] [Machine Code Instructions (video)](https://www.youtube.com/watch?v=Mv2XQgpbTNE)
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## Algorithmic complexity / Big-O / Asymptotic analysis
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## 알고리즘 복잡도 / Big-O / 점근적 분석
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- nothing to implement
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- [ ] [Harvard CS50 - Asymptotic Notation (video)](https://www.youtube.com/watch?v=iOq5kSKqeR4)
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- [ ] [Big O Notations (general quick tutorial) (video)](https://www.youtube.com/watch?v=V6mKVRU1evU)
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@ -641,7 +641,7 @@ My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (
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- contiguous in memory, so proximity helps performance
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- space needed = (array capacity, which is >= n) * size of item, but even if 2n, still O(n)
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- ### Linked Lists
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- ### 링크드 리스트
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- [ ] Description:
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- [ ] [Singly Linked Lists (video)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists)
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- [ ] [CS 61B - Linked Lists (video)](https://www.youtube.com/watch?v=sJtJOtXCW_M&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=5)
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@ -674,12 +674,12 @@ My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (
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- [Description (video)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists)
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- No need to implement
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- ### Stack
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- ### 스택
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- [ ] [Stacks (video)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks)
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- [ ] [Using Stacks Last-In First-Out (video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-stacks-last-first-out/149042/177120-4.html)
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- [ ] Will not implement. Implementing with array is trivial.
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- ### Queue
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- ### 큐
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- [ ] [Using Queues First-In First-Out(video)](https://www.lynda.com/Developer-Programming-Foundations-tutorials/Using-queues-first-first-out/149042/177122-4.html)
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- [ ] [Queue (video)](https://www.coursera.org/learn/data-structures/lecture/EShpq/queue)
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- [ ] [Circular buffer/FIFO](https://en.wikipedia.org/wiki/Circular_buffer)
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@ -700,7 +700,7 @@ My flashcard database in Anki format: https://ankiweb.net/shared/info/25173560 (
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- dequeue: O(1) (linked list and array)
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- empty: O(1) (linked list and array)
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- ### Hash table
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- ### 해쉬 테이블
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- [ ] Videos:
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- [ ] [Hashing with Chaining (video)](https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8)
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- [ ] [Table Doubling, Karp-Rabin (video)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
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