# 코딩 인터뷰 대학(Coding Interview University)

> 나는 원래 이것을 소프트웨어 엔지니어가 되기 위한 짧은 연구 목록으로 만들었다.
> 그러나 지금 당신이 볼수 있듯이 이 목록은 매우 커졌다. 이 목록을 숙지 한 후, 
> [나는 아마존에 소프트웨어 엔지니어로 채용됐다](https://startupnextdoor.com/ive-been-acquired-by-amazon/?src=ciu)!
> 당신은 아마 내가 한 것처럼 많이 공부할 필요는 없을 것이다. 어쨌든 당신이 필요로 하는 모든 것은 여기에 있다.
>
> 여기에 나열된 목록들은 아마존, 페이스북, 구글, 마이크로소프트 같은 거대 기업을 포함한 거의 모든 소프트웨어 회사의 인터뷰를 준비하는데에 도움이 될것이다.
> 
>
> *행운을 빈다!*

번역:

- [베트남어](translations/README-vi.md)
- [브라질 포르투갈어](translations/README-ptbr.md)
- [스페인어](translations/README-es.md)
- [중국어](translations/README-cn.md)

진행 중인 번역

- [그리스어](https://github.com/jwasham/coding-interview-university/issues/166)
- [러시아어](https://github.com/jwasham/coding-interview-university/issues/87)
- [말라얄람어](https://github.com/jwasham/coding-interview-university/issues/239)
- [바하사 인도네시아어](https://github.com/jwasham/coding-interview-university/issues/101)
- [아랍어](https://github.com/jwasham/coding-interview-university/issues/98)
- [우르두어](https://github.com/jwasham/coding-interview-university/issues/140)
- [우크라이나어](https://github.com/jwasham/coding-interview-university/issues/106)
- [이탈리아어](https://github.com/jwasham/coding-interview-university/issues/170)
- [일본어](https://github.com/jwasham/coding-interview-university/issues/257)
- [태국어](https://github.com/jwasham/coding-interview-university/issues/156)
- [터키어](https://github.com/jwasham/coding-interview-university/issues/90)
- [텔루구어](https://github.com/jwasham/coding-interview-university/issues/117)
- [폴란드어](https://github.com/jwasham/coding-interview-university/issues/122)
- [프랑스어](https://github.com/jwasham/coding-interview-university/issues/89)
- [한국어](https://github.com/jwasham/coding-interview-university/issues/118)
- [히브리어](https://github.com/jwasham/coding-interview-university/issues/82)
- [힌디어](https://github.com/jwasham/coding-interview-university/issues/81)


## 코딩 인터뷰 대학이란?

코딩 인터뷰 대학은 웹 개발자(컴퓨터공학 학위 없이 독학)에서 구글의 소프트웨어 엔지니어가 되기 위한 나의 몇 달 간의 공부 계획이다.

![Coding at the whiteboard - from HBO's Silicon Valley](https://dng5l3qzreal6.cloudfront.net/2016/Aug/coding_board_small-1470866369118.jpg)

이 기나긴 리스트는 **구글 코칭 노트**에서 선별되고 확장된 것으로 여러분이 알아야 할 내용이다. 맨 아래에는 인터뷰에 등장하거나 문제를 푸는 데에 도움이 될 만한 추가적인 내용이 있다. 많은 내용이 Steve Yegge의  "[Get that job at Google](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html)"이라는 책에서 나왔으며, 때때로 구글 코칭 노트의 내용을 그대로 담고있기도 하다.

나는 Yegge의 추천으로부터 여러분이 알아야만 할 내용들을 추려내었다. 구글과의 연락으로 얻은 정보를 바탕으로 그의 추천내용을 수정하였다. 이 리스트는 신입 소프트웨어 엔지니어, 혹은 소프트웨어/웹 개발에서 소프트웨어 엔지니어링(컴퓨터과학 지식이 필요한)으로 전환하는 사람들을 위한 것이다

만약 당신이 여러 해의 소프트웨어 엔지니어링 경력이 있다면, 더 어려운 인터뷰가 예상된다. [더 보기](https://googleyasheck.com/what-you-need-to-know-for-your-google-interview-and-what-you-dont/).

만약 당신이 여러 해의 소프트웨어/웹 개발 경험을 가지고 있다면, 구글은 소프트웨어 엔지니어링을 소프트웨어/웹 개발과 다르게 바라보고 있으며 컴퓨터과학 지식을 요구한다는 사실에 주목하도록 하자.

신뢰할만한 엔지니어, 혹은 시스템 엔지니어가 되고 싶다면 선택적 주제 목록(네트워크, 보안 등)을 더 공부하도록 하자.

---

## 목차

- [코딩 인터뷰 대학이란?](#코딩-인터뷰-대학이란)
- [Why use it?](#why-use-it)
- [How to use it?](#how-to-use-it)
- [당신은 충분히 똑똑합니다](#당신은-충분히-똑똑합니다)
- [영상 자료에 관하여](#영상-자료에-관하여)
- [인터뷰 과정 & 전반적인 인터뷰 준비 과정](#인터뷰-과정--전반적인-인터뷰-준비-과정)
- [인터뷰를 위한 언어 고르기](#인터뷰를-위한-언어-고르기)
- [도서 목록](#도서-목록)
- [시작하기 전에](#시작하기-전에)
- [다루지 않을 것](#다루지-않을-것)
- [선수 지식](#선수-지식)
- [하루 하루의 계획](#하루-하루의-계획)
- [알고리즘 복잡도 / Big-O / 점근적 분석](#알고리즘-복잡도--big-o--점근적-분석)
- [자료구조](#자료구조)
    - [배열](#배열)
    - [링크드 리스트](#링크드-리스트)
    - [스택](#스택)
    - [큐](#큐)
    - [해쉬 테이블](#해쉬-테이블)
- [추가 지식](#more-knowledge)
    - [이진 탐색/이진 검색](#binary-search)
    - [비트 연산](#bitwise-operations)
- [트리](#trees)
    - [트리 - 배경지식](#trees---notes--background)
    - [이진 탐색 트리(BST)](#binary-search-trees-bsts)
    - [힙 / 우선순위 큐 / 이진 힙](#heap--priority-queue--binary-heap)
    - 균형 탐색 트리 (간단한 개념)
    - 트리 순회: 전위 순회, 중위 순회, 후위 순회, 너비 우선 탐색(BFS), 깊이 우선 탐색(DFS)
- [정렬](#sorting)
    - 선택 정렬
    - 삽입 정렬
    - 힙 정렬
    - 퀵 정렬
    - 병합 정렬
- [그래프](#graphs)
    - 방향 그래프
    - 무방향 그래프
    - 인접 행렬
    - 인접 리스트
    - 그래프 순회: 너비 우선 탐색(BFS), 깊이 우선 탐색(DFS)
- [더 많은 지식](#even-more-knowledge)
    - [재귀](#recursion)
    - [동적 프로그래밍](#dynamic-programming)
    - [객체 지향 프로그래밍](#object-oriented-programming)
    - [디자인 패턴](#design-patterns)
    - [조합 & 확률](#combinatorics-n-choose-k--probability)
    - [NP와 NP-완전, 그리고 근사 알고리즘](#np-np-complete-and-approximation-algorithms)
    - [캐시](#caches)
    - [프로세스와 쓰레드](#processes-and-threads)
    - [논문](#papers)
    - [테스트](#테스트)
    - [스케줄링](#scheduling)
    - [시스템 루틴의 구현](#implement-system-routines)
    - [문자열 검색 & 조작](#string-searching--manipulations)
    - [트라이](#tries)
    - [부동 소수점](#floating-point-numbers)
    - [유니코드](#unicode)
    - [엔디언(Endianness)](#endianness)
- [네트워크](#networking)
- [시스템 디자인, 확장성, 데이터 핸들링](#system-design-scalability-data-handling) (4년 이상 경력자를 위한 주제)
- [최종 리뷰](#final-review)
- [코딩 문제 연습](#coding-question-practice)
- [코딩 연습 / 도전](#coding-exerciseschallenges)
- [인터뷰가 얼마 남지 않았을 때](#once-youre-closer-to-the-interview)
- [이력서](#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)
- [직업을 갖게 되었을 때](#once-youve-got-the-job)

---------------- Everything below this point is optional ----------------

- [추가 도서](#additional-books)
- [추가 주제](#additional-learning)
    - [컴파일러](#compilers)
    - [부동 소수점 수](#floating-point-numbers)
    - [유니코드](#unicode)
    - [엔디언](#endianness)
    - [Emacs 와 vi(m)](#emacs-and-vim)
    - [유닉스 명령어 도구](#unix-command-line-tools)
    - [정보 이론](#information-theory)
    - [패리티 & 해밍코드](#parity--hamming-code)
    - [엔트로피](#entropy)
    - [암호기법](#cryptography)
    - [압축](#compression)
    - [네트워크](#networking) (if you have networking experience or want to be a systems engineer, expect questions)
    - [컴퓨터 보안](#computer-security)
    - [가비지 콜렉션](#garbage-collection)
    - [병렬 프로그래밍](#parallel-programming)
    - [메세징, 직렬화, 그리고 큐잉 시스템](#messaging-serialization-and-queueing-systems)
    - [고속 푸리에 변환(FFT)](#fast-fourier-transform)
    - [블룸 필터](#bloom-filter)
    - [HyperLogLog](#hyperloglog)
    - [Locality-Sensitive Hashing](#locality-sensitive-hashing)
    - [van Emde Boas 트리](#van-emde-boas-trees)
    - [Augmented Data Structures](#augmented-data-structures)
    - [트라이(Tries)](#tries)
    - [N-ary (K-ary, M-ary) trees](#n-ary-k-ary-m-ary-trees)
    - [균형 탐색 트리](#balanced-search-trees)
        - AVL 트리
        - Splay 트리
        - 레드블랙 트리(RBT)
        - 2-3 탐색 트리
        - 2-3-4 트리(aka 2-4 트리)
        - N-ary (K-ary, M-ary) 트리
        - B-트리
    - [k-D 트리](#k-d-trees)
    - [스킵 리스트](#skip-lists)
    - [네트워크 플로우(유량)](#network-flows)
    - [분리집합 & 유니온 파인드(Disjoint Sets & Union Find)](#disjoint-sets--union-find)
    - [빠른 프로세싱을 위한 수학](#math-for-fast-processing)
    - [트립](#treap)
    - [선형 계획법](#linear-programming)
    - [기하학, 볼록 껍질](#geometry-convex-hull)
    - [이산수학](#discrete-math)
    - [기계학습](#machine-learning)
- [몇몇 주제에 대한 세부사항](#additional-detail-on-some-subjects)
- [영상 자료](#영상-자료)
- [컴퓨터 과학 강의들](#computer-science-courses)
- [라이센스](#라이센스)

---

## Why use it?

나는 구글 인터뷰를 준비하기 위해 이 계획을 따랐다. 1997년 부터 나는 웹과 서비스를 개발하고 스타트업을 세웠다. 나는 컴퓨터과학이 아닌 경제학 학위를 가지고 있다.
나의 커리어는 굉장히 성공적이어왔지만, 나는 구글에서 일하고 싶었다. 나는 더 큰 시스템을 다루고 컴퓨터 시스템, 알고리즘 효율, 자료구조 퍼포먼스, 저급 언어 등과 그 것들이 어떻게 작동하는지에 대하여
이해하고 싶었다. 그리고 당신이 그런 것들을 모른다면 구글은 당신을 채용하지 않을 것이다.

내가 이 프로젝트를 시작했을 때, 나는 힙스택, Big-O, 트리, 그래프 운행 등에 대하여 전혀 아는 바가 없었다.
만약 내가 정렬 알고리즘을 코딩해야했다면, 나는 그리 잘 하지 못했을 것이다.
모든 사용했던 모든 자료 구조는 언어 안에서 구현 되어 있던 것들이고, 나는 그 것들이 보이는 것 아래서 어떻게 작동하고 있는지 알지 못했다.
나는 진행 중인 프로세스가 메모리 부족 에러를 메세지를 보내지 않는 한 메모리를 관리할 필요가 없었고, 나는 회피방법을 찾아야만 했다.
나는 몇몇 다차원 배열이나 연관 배열을 사용해왔지만, 자료구조를 처음부터 구현해본 적은 없었다.

하지만 이 공부 계획을 진행하면서 나는 내가 고용될 것이라는 자신감을 갖게 되었다. 이 것은 내게 여러 달이 필요한 긴 계획이다.
만약 당신이 이 중 많은 내용에 익숙하다면 시간은 훨씬 덜 들 것이다.

## How to use it?

아래의 모든 것은 대략적인 개요이며 당신은 위에서 아래 순서대로 진행해야 한다.

진행상황을 확인하기 위한 목록를 포함하여, 나는 Github'special markdown flavor를 사용하고 있다.

**새 브랜치를 만들어서 중괄호에 x표를 넣는 식으로 항목을 체크하라: [x]**

	브랜치를 포크하고 아래의 명령을 따라라

`git checkout -b progress`

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

`git fetch --all`

    끝났으면 박스에 x로 체크하라

`git add . `

`git commit -m "Marked x" `

`git rebase jwasham/master `

`git push --force `

[Github-flavored markdown에 대하여](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown)


## 당신은 충분히 똑똑합니다
- 구글 엔지니어들은 똑똑합니다. 하지만 그들 조차도 자신들의 지적 능력면에 대해서 불안감을 갖기 일쑤입니다.
- [천재 프로그래머에 대한 미신(迷信)](https://www.youtube.com/watch?v=0SARbwvhupQ)
- [위험한 홀로서기: 테크 산업의 보이지 않는 괴물들의 전쟁](https://www.youtube.com/watch?v=1i8ylq4j_EY)

## 영상 자료에 관하여

몇몇 영상들은 Cousera, Edx, Lynda.com 클래스에 등록하여야만 시청이 가능합니다. 이것들은 MOOCs라고 불리는데요.
강의가 없는 경우에는 몇 달 동안 기다려야 할 수도 있습니다. Lynda.com 강좌들은 무료가 아닙니다.

    여러분이 YouTube 온라인 강의 동영상과 같이 무료이고 항상 접근 가능한 동영상 소스들을 추가해주면 정말 감사하겠습니다.
    저는 대학 강의 듣는 것을 좋아합니다.

## 인터뷰 과정 & 전반적인 인터뷰 준비 과정

- [ ] 비디오:

    - [ ] [구글에서 일하게 되는법: 기술 인터뷰 준비하기 (video)](https://www.youtube.com/watch?v=ko-KkSmp-Lk)
    - [ ] [구글에서 일하게 되는법: 코딩/기술 인터뷰 예시 (video)](https://www.youtube.com/watch?v=XKu_SEDAykw)
    - [ ] [구글에서 일하게 되는법 - 지원자 코칭 시간 (video)](https://www.youtube.com/watch?v=oWbUtlUhwa8&feature=youtu.be)
    - [ ] [구글 리크루터들이 공유한 기술 인터뷰 팁들 (video)](https://www.youtube.com/watch?v=qc1owf2-220&feature=youtu.be)
    - [ ] [구글에서 일하게 되는법: 기술 레쥬메 준비 (video)](https://www.youtube.com/watch?v=8npJLXkcmu8)

- [ ] 읽을 거리들:

    - [ ] [구글러 되기 3단계](http://www.google.com/about/careers/lifeatgoogle/hiringprocess/)
    - [ ] [구글에서 그 직업 갖기](http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html)
      - 이 글에서 저자가 언급한 당신이 알아야 할 모든 것들은 이 리스트 아래에 소개되어 있습니다.
    - [ ] _(아주 오래됨)_ [구글에 취업하는 방법, 인터뷰 질문들, 채용 절차](http://dondodge.typepad.com/the_next_big_thing/2010/09/how-to-get-a-job-at-google-interview-questions-hiring-process.html)
    - [ ] [화상통화 인터뷰 질문들](http://sites.google.com/site/steveyegge2/five-essential-phone-screen-questions)


- [ ] 준비 코스:
    - [ ] [소프트웨어 엔지니어 인터뷰 대공개 (유료 강좌)](https://www.udemy.com/software-engineer-interview-unleashed):
        - 전직 구글 엔지니어로부터 당신이 어떻게 소프트웨어 엔지니어 인터뷰를 준비해야 하는지 배우게 됩니다.

- [ ] 부가물 (구글이 추천하지않은 내가 더한 것들):
    - [ ] [ABC: 항상 코딩 하라](https://medium.com/always-be-coding/abc-always-be-coding-d5f8051afce2#.4heg8zvm4)
    - [ ] [학위 없이 구글에 들어가기 4단계](https://medium.com/always-be-coding/four-steps-to-google-without-a-degree-8f381aa6bd5e#.asalo1vfx)
    - [ ] [화이트 보드 쓰기](https://medium.com/@dpup/whiteboarding-4df873dbba2e#.hf6jn45g1)
    - [ ] [채용, 관리, 문화에 대한 구글의 생각](http://www.kpcb.com/blog/lessons-learned-how-google-thinks-about-hiring-management-and-culture)
    - [ ] [코딩 인터뷰에서 화이트 보드 효율적으로 쓰기](http://www.coderust.com/blog/2014/04/10/effective-whiteboarding-during-programming-interviews/)
    - [ ] 코딩 인터뷰 정복 Set 1:
      - [ ] [Gayle L McDowell - 코딩 인터뷰 정복 (영상)](https://www.youtube.com/watch?v=rEJzOhC5ZtQ)
      - [ ] [저자와 함께하는 코딩 인터뷰 정복 (영상)](https://www.youtube.com/watch?v=aClxtDcdpsQ)
    - [ ] Big 4에 취업하는 방법:
      - [ ] ['Big 4에 취업하는 방법 - Amazon, Facebook, Google & Microsoft' (영상)](https://www.youtube.com/watch?v=YJZCUhxNCv8)
    - [ ] [구글 인터뷰 실패기](http://alexbowe.com/failing-at-google-interviews/)


## 인터뷰를 위한 언어 고르기

인터뷰때 사용할 언어 고르는 법에 대해 짧은 글을 하나 썼습니다: [구글 인터뷰를 위한 언어 고르기](https://googleyasheck.com/important-pick-one-language-for-the-google-interview/)

인터뷰때에 당신이 쓰기에 편한 언어를 선택해도 되지만, 구글 인터뷰에 선호되는 언어들은 다음과 같습니다.


- C++
- Java
- Python


아래 언어들을 사용할 수 있지만 주의하여야 합니다.


- JavaScript
- Ruby


당신은 당신의 언어에 익숙하고 그 언어에 대해 잘 알아야 합니다.

언어 선택을 도와줄 만한 읽을 거리들

- http://www.byte-by-byte.com/choose-the-right-language-for-your-coding-interview/
- http://blog.codingforinterviews.com/best-programming-language-jobs/
- https://www.quora.com/What-is-the-best-language-to-program-in-for-an-in-person-Google-interview


[프로그래밍 언어 참고목록](programming-language-resources.md)

제가 공부하고 있는 C, C++, Python 강의를 아래서 볼 수 있습니다. 아래를 보시면 관련된 책들이 몇 개 있습니다.


## 도서 목록

아래의 목록은 내가 공부했던 책들보다는 적다. 당신의 시간을 절약하기 위해 몇몇 책들은 생략하였다.


### 인터뷰 준비를 위해서

- [ ] [Programming Interviews Exposed: Secrets to Landing Your Next Job, 2nd Edition](http://www.wiley.com/WileyCDA/WileyTitle/productCd-047012167X.html)
    - C++ 과 JAVA 문제의 답변을 위해서
    - 구글 지원자를 위해 추천되었기 때문에
    - Cracking the Coding Interview 책을 위한 좋은 사전학습용 책이기 때문에
    - 어렵지 않고, 당신이 인터뷰에서 마주할 대부분의 문제들 보다 쉽기 때문에
- [ ] [Cracking the Coding Interview, 6th Edition](http://www.amazon.com/Cracking-Coding-Interview-6th-Programming/dp/0984782850/)
    - JAVA 문제의 답변을 위해서
    - Google Careers site에서 추천되었기 때문에 [Google Careers site](https://www.google.com/about/careers/how-we-hire/interview/)
    - 만일 당신이 다른 사람들의 "The Google Resume"를 참고자료로 봤다면, "Cracking the Coding Interview"는 그것을 대신할 수 있는 책이다.


만일 당신이 많은 여유 시간이 있다면:

- [ ] [Elements of Programming Interviews](https://www.amazon.com/Elements-Programming-Interviews-Insiders-Guide/dp/1479274836)
    - 모든 코드가 C++로 되어있다, 만일 당신의 인터뷰에서 C++를 사용하길 고려한다면 정말 좋은 책이다.
    - 일반적인 문제들을 해결하기 위해 좋은 책이다.


### 컴퓨터 구조

준비기간이 짧을 때,

- [ ] [Write Great Code: Volume 1: Understanding the Machine](https://www.amazon.com/Write-Great-Code-Understanding-Machine/dp/1593270038)
    - 이 책은 2004년에 출판된 다소 구식의 책이지만, 간략히 컴퓨터를 이해하는 데에 훌륭한 자료입니다.
    - 이 책의 저자는 HLA를 발명했습니다. 그래서 회의적인 시선으로 HLA에 대해 언급하고 예로 듭니다. 널리 읽히지는 않지만, 어셈블리가 어떻게 생겼는 지를 보여주는 좋은 예입니다.
    - 이 장들은 당신에게 탄탄한 기초를 세워줄 것입니다:
        - 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

만약에 시간적 여유가 좀 더 있다면 아래 서적을 읽어보는 것을 권유합니다.
- [ ] [Computer Architecture, Fifth Edition: A Quantitative Approach](https://www.amazon.com/dp/012383872X/)
    - For a richer, more up-to-date (2011), but longer treatment

### 언어 구체적

**인터뷰를 위해 당신의 언어를 선택하여야 합니다 (윗글 참조)** 아래는 제가 추천하는 언어들입니다. 이 언어들중에 부연설명이나 부가 자료들이 있다면 나눠 주세요.

이 중 하나를 읽으려면 코딩 문제 푸는 데 필요한 데이터 구조 및 알고리즘 지식이 있어야합니다.

**You can skip all the video lectures in this project**, unless you'd like a review.

[Additional language-specific resources here.](programming-language-resources.md)

### C++

나는 아래의 두 책들을 읽지 않았습니다. 하지만 Sedgewick이 높게 평가한 책들입니다. 그는 정말 대단한 사람입니다.


- [ ] [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/)

C++에 대한 더 나은 추천 책이 있다면 알려주십시오. 포괄적인 자료를 찾고 있습니다.

### Java

- [ ] [Algorithms (Sedgewick and Wayne)](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X/)
    - videos with book content (and Sedgewick!):
        - [Algorithms I](https://www.youtube.com/user/algorithmscourses/playlists?view=50&sort=dd&shelf_id=2)
        - [Algorithms II](https://www.youtube.com/user/algorithmscourses/playlists?shelf_id=3&view=50&sort=dd)

OR:

- [ ] [Data Structures and Algorithms in Java](https://www.amazon.com/Data-Structures-Algorithms-Michael-Goodrich/dp/1118771338/)
    - by Goodrich, Tamassia, Goldwasser
    - UC버클리 대학의  CS입문 과정의 선택 텍스트로 사용됨
    - 아래에서 Python 버전에 대한 나의 책 보고서를 참조하십시오. 이 책은 동일한 주제를 다루고 있습니다.

### Python

- [ ] [Data Structures and Algorithms in Python](https://www.amazon.com/Structures-Algorithms-Python-Michael-Goodrich/dp/1118290275/)
    - by Goodrich, Tamassia, Goldwasser
    - 나는 이 책을 사랑한다. 이 책은 모든 것을 다룬다.
    - Pythonic code
    - 나의 열렬한 서적 보고서: https://googleyasheck.com/book-report-data-structures-and-algorithms-in-python/


### 선택 도서

**어떤 사람들은 이 책들을 추천한다. 하지만 만약 당신이 소프트웨어 엔지니어링 분야에 오랜 경험이 있고, 그로 인해 훨씬 더 어려운 인터뷰를 볼 것이라 생각하지 않는다면, 나는 이 책들을 공부하는 것이 너무 과하다고 생각한다:**

- [ ] [Algorithm Design Manual](http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202) (Skiena)
    - As a review and problem recognition
    - The algorithm catalog portion is well beyond the scope of difficulty you'll get in an interview.
    - This book has 2 parts:
        - class textbook on data structures and algorithms
            - pros:
                - is a good review as any algorithms textbook would be
                - nice stories from his experiences solving problems in industry and academia
                - code examples in C
            - cons:
                - can be as dense or impenetrable as CLRS, and in some cases, CLRS may be a better alternative for some subjects
                - chapters 7, 8, 9 can be painful to try to follow, as some items are not explained well or require more brain than I have
                - don't get me wrong: I like Skiena, his teaching style, and mannerisms, but I may not be Stony Brook material.
        - algorithm catalog:
            - this is the real reason you buy this book.
            - about to get to this part. Will update here once I've made my way through it.
    - To quote Yegge: "More than any other book it helped me understand just how astonishingly commonplace
        (and important) graph problems are – they should be part of every working programmer's toolkit. The book also
        covers basic data structures and sorting algorithms, which is a nice bonus. But the gold mine is the second half
        of the book, which is a sort of encyclopedia of 1-pagers on zillions of useful problems and various ways to solve
        them, without too much detail. Almost every 1-pager has a simple picture, making it easy to remember. This is a
        great way to learn how to identify hundreds of problem types."
    - Can rent it on kindle
    - Half.com is a great resource for textbooks at good prices.
    - Answers:
        - [Solutions](http://www.algorithm.cs.sunysb.edu/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition))
        - [Solutions](http://blog.panictank.net/category/algorithmndesignmanualsolutions/page/2/)
    - [Errata](http://www3.cs.stonybrook.edu/~skiena/algorist/book/errata)

- [ ] [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.
    - To quote Yegge: "But if you want to come into your interviews *prepped*, then consider deferring your application until you've made your way through that book."
    - Half.com is a great resource for textbooks at good prices.
    - aka CLR, sometimes CLRS, because Stein was late to the game

- [ ] [Programming Pearls](http://www.amazon.com/Programming-Pearls-2nd-Jon-Bentley/dp/0201657880)
    - The first couple of chapters present clever solutions to programming problems (some very old using data tape) but
      that is just an intro. This a guidebook on program design and architecture, much like Code Complete, but much shorter.

- ~~"Algorithms and Programming: Problems and Solutions" by Shen~~

    - A fine book, but after working through problems on several pages I got frustrated with the Pascal, do while loops, 1-indexed arrays, and unclear post-condition satisfaction results.

    - Would rather spend time on coding problems from another book or online coding problems.


## 시작하기 전에

이 문서는 몇 달간 계속 업데이트 되고 있으며, 그런 이유로, 내가 감당할 수 없어지기 시작한 듯하다.

내가 저지른 몇 가지 실수들을 소개한다. 이를 통해 당신은 이 과정을 좀 더 효과적으로 진행할 수 있기를 바란다.

### 1. 당신은 이것을 다 기억하지 못할 것이다.

나는 수 시간의 비디오를 보고 방대한 양의 노트를 작성했지만, 몇 달 뒤에는 대부분의 내용을 기억하지 못했다. 나는 3일 동안 내가 작성한 노트를 보고 flashcard를 만들면서 내용들을 다시 검토해야 했다.

꼭 읽고 내가 한 실수들을 반복하지 않길 바란다.

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

### 2. Flashcard를 사용하자.

이 문제를 해결하기 위해 나는 2가지 종류(일반적인 내용, 코드)의 flashcard를 보관하고 추가할 수 있는 작은 사이트를 만들었다. 각 카드는 다른 서식을 가지고 있다.

이 사이트는 모바일에 최적화 되어있기 때문에 내 전화기나 태블릿 어디에서든 이를 확인할 수 있다.

당신만의 카드를 만들어보자(무료로):

- [Flashcard 사이트 repo](https://github.com/jwasham/computer-science-flash-cards)
- [내 flashcard 데이터베이스 (old - 1200 cards)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham.db):
- [내 flashcard 데이터베이스 (new - 1800 cards)](https://github.com/jwasham/computer-science-flash-cards/blob/master/cards-jwasham-extreme.db):

앞에서도 언급했듯이 나는 불필요하게 많은 것을 공부하려고 했고, 내 카드의 내용들은 어셈블리 언어와 Python의 자잘한 지식들부터 기계 학습과 통계학까지 넘나들게 되었다. 결국 구글이 요구하는 것보다 훨씬 멀리 가버리고 말았다.

**flashcard에 대한 참고사항:** 답을 할 수 있더라도 처음부터 안다고 표시하지 말자. 정확히 알기 전까지는 같은 카드를 보고 여러 번 답변할 수 있어야한다.
반복 학습을 통해 해당 지식은 당신의 뇌에 깊이 각인될 것이다.



나의 flashcard site를 사용하는 대신 [Anki](http://ankisrs.net/)를 사용해도 된다. 나는 이 것을 여러 번 추천받았다. 이것은 당신이 기억하는 것을 돕기 위해 반복적인 시스템을 사용한다.

이것은 사용자 친화적이며, 모든 플랫폼에서 사용가능하다. 또한 클라우드 동기화 시스템을 제공한다. 이것은 iOS에서는 $25이지만 다른 플랫폼에서는 무료로 사용 가능하다.

Anki format의 내 flashcard 데이터베이스: https://ankiweb.net/shared/info/25173560 (thanks [@xiewenya](https://github.com/xiewenya))

### 3. 검토, 검토, 검토

나는 ASCII, OSI 구조, Big-O 표기법 등에 관한 일련의 치트시트를 만들어 놓고, 여유 시간이 날 때마다  공부한다.

30분 동안 프로그래밍 문제를 해결하고, flashcard를 살펴보자.

### 4. 집중

주의를 산만하게 만드는 많은 것이 있으며, 이것들은 우리의 귀중한 시간을 뺏어간다. 주의를 집중하는 것은 힘든 일이다.

## 다루지 않을 것

이 큰 주제들은 모두 Google 인터뷰 코칭 노트에서 개인적인 to-do list로 시작되었다.
이 기술들은 널리 퍼져 있는 기술이지만, Google 인터뷰 코칭 노트에서 언급 되지 않았다:

- SQL
- Javascript
- HTML, CSS, 그리고 다른 프론트엔드 기술들


## 하루 하루의 계획

어떤 주제들은 하루가 걸리고, 어떤 것들은 며칠이 걸릴 것이다.
또 어떤것은 구현할 것들이 없이 그냥 배우는 것들이다.

아래 리스트에 있는 것에서 매일 하나의 주제를 택했고, 그 주제에 대한 강의를 보고, 구현을 했다:
- C - 인자를 가지는 구조체와 함수 사용
- C++ - 빌트인 타입 사용하지 않음
- C++ - 링크리스트를 위한 STL's std::list 같은 빌트인 타입 사용
- Python - 빌트인 타입 사용 (파이선 연습을 계속 하려고)
- 제대로 하고 있는지 테스트를 했고 가끔은 간단한 assert() 사용
- 당신은 아마 자바나 그 어떤 언어를 이용하겠지만 이것은 그냥 내 것들이다.

당신은 이것을 다 할 필요는 없다. 단지 [인터뷰를 위한 하나의 언어를 할 것.](#인터뷰를 위한 언어를 하나 골라 두어라).

왜 이 모든것을 코딩해야 하는가?
- 나는 이것에 미칠때까지 연습하고 또 연습했고, 아무런 문제 없이 할 수 있게 되었다 (어떤 것들은 다양한 케이스가 있고 이것을 기억하기 위해 기록을 보관했다.)
- 있는 그대로의 제한 속에서 연습 (garbage collection의 도움없이 메모리 할당과 해지 (파이선 빼고))
- 빌트인 타입을 사용하여 나는 빌트인 도구에 대한 경험이 있게 되었다. (내 프로젝트의 링크 리스트 구현은 쓰지 않을 예정)

모든 주제에 대한 모든 것을 할 수 없지만 나는 노력했다.

나의 코드를 여기서 확인하세요:

 - [C] (https://github.com/jwasham/practice-c)
 - [C++] (https://github.com/jwasham/practice-cpp)
 - [Python] (https://github.com/jwasham/practice-python)


당신은 모든 알고리즘에 대해서 기억할 필요는 없다.

컴퓨터에 코딩하지 말고 와이트보드나 종이에 적어보아라. 인풋 값으로 샘플 테스트를 해 보아라. 그리고 컴퓨터로 테스트해 보아라.

## 선수 지식

- [ ] **Learn C**
    - C 는 어디에나 있다. 당신은 책이나 강의, 비디오 등 공부하는 동안 모든 곳에서 예제를 볼 것이다.
    - [ ] [C Programming Language, Vol 2](https://www.amazon.com/Programming-Language-Brian-W-Kernighan/dp/0131103628)
        - 이 책은 분량이 적은 책이지만 C 를 잘 다룰 수 있게 해 줄 것이다. 또한 조금만 연습하더라도 연습량에 비해 빠르게 배울 수 있을 것이다. C 를 이해하는 것은 프로그램과 메모리가 어떻게 돌아가는지 이해하는 것을 도와준다.
        - [answers to questions](https://github.com/lekkas/c-algorithms)


- [ ] **How computers process a program:**
    - [ ] [How does CPU execute program (video)](https://www.youtube.com/watch?v=42KTvGYQYnA)
    - [ ] [Machine Code Instructions (video)](https://www.youtube.com/watch?v=Mv2XQgpbTNE)

## 알고리즘 복잡도 / Big-O / 점근적 분석
- nothing to implement
- [ ] [Harvard CS50 - Asymptotic Notation (video)](https://www.youtube.com/watch?v=iOq5kSKqeR4)
- [ ] [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)
- [ ] 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/)
- [ ] [Orders of Growth (video)](https://class.coursera.org/algorithmicthink1-004/lecture/59)
- [ ] [Asymptotics (video)](https://class.coursera.org/algorithmicthink1-004/lecture/61)
- [ ] [UC Berkeley Big O (video)](https://youtu.be/VIS4YDpuP98)
- [ ] [UC Berkeley Big Omega (video)](https://youtu.be/ca3e7UVmeUc)
- [ ] [Amortized Analysis (video)](https://www.youtube.com/watch?v=B3SpQZaAZP4&index=10&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN)
- [ ] [Illustrating "Big O" (video)](https://class.coursera.org/algorithmicthink1-004/lecture/63)
- [ ] TopCoder (includes recurrence relations and master theorem):
    - [Computational Complexity: Section 1](https://www.topcoder.com/community/data-science/data-science-tutorials/computational-complexity-section-1/)
    - [Computational Complexity: Section 2](https://www.topcoder.com/community/data-science/data-science-tutorials/computational-complexity-section-2/)
- [ ] [Cheat sheet](http://bigocheatsheet.com/)


    If some of the lectures are too mathy, you can jump down to the bottom and
    watch the discrete mathematics videos to get the background knowledge.

## 자료구조

- ### 배열
    - 자동 리사이징 벡터 구현하기
    - [ ] 설명:
        - [배열 (영상)](https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays)
        - [UCBerkley CS61B - 선형과 다차원 배열 (영상)](https://youtu.be/Wp8oiO_CZZE?t=15m32s)
        - [배열 기본 (영상)](https://archive.org/details/0102WhatYouShouldKnow/02_04-basicArrays.mp4)
        - [다차원 배열 (영상)](https://archive.org/details/0102WhatYouShouldKnow/02_05-multidimensionalArrays.mp4)
        - [동적 배열 (영상)](https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays)
        - [가변 배열 (영상)](https://www.youtube.com/watch?v=1jtrQqYpt7g)
        - [가변 배열 (영상)](https://archive.org/details/0102WhatYouShouldKnow/02_06-jaggedArrays.mp4)
        - [배열 리사이징 (영상)](https://archive.org/details/0102WhatYouShouldKnow/03_01-resizableArrays.mp4)
    - [ ] 벡터 구현하기 (자동 리사이징을 포함한 동적 배열):
        - [ ] 배열, 포인터 및 인덱싱 대신하여 특정 인덱스에 접근하는 포인터 연산을 통한 코딩 연습
        - [ ] 메모리 할당을 포함한 새 배열
            - 배열 메소드 등의 기능을 활용하지 않으면서 정수 배열에 메모리를 할당할 수 있어야 함
            - 16으로 시작하거나 시작하는 숫자가 크다면 2의 제곱수(16, 32, 64, 128)로 시작
        - [ ] size() - 항목의 개수
        - [ ] capacity() - 들어갈 수 있는 항목의 최대 개수number of items it can hold
        - [ ] is_empty()
        - [ ] at(index) - 인덱스에 있는 항목을 돌려주고, 인덱스가 범위 밖이면 에러를 냄
        - [ ] push(item)
        - [ ] insert(index, item) - index에 item을 삽입하고 기존 인덱스의 값부터 쭉 오른쪽으로 쉬프트
        - [ ] prepend(item) - 맨 앞에 원소를 삽입
        - [ ] pop() - 마지막 원소를 삭제하고 값을 돌려준다
        - [ ] delete(index) - delete item at index, shifting all trailing elements left
        - [ ] remove(item) - looks for value and removes index holding it (even if in multiple places)
        - [ ] find(item) - looks for value and returns first index with that value, -1 if not found
        - [ ] resize(new_capacity) // private function
            - when you reach capacity, resize to double the size
            - when popping an item, if size is 1/4 of capacity, resize to half
    - [ ] Time
        - O(1) to add/remove at end (amortized for allocations for more space), index, or update
        - O(n) to insert/remove elsewhere
    - [ ] Space
        - contiguous in memory, so proximity helps performance
        - space needed = (array capacity, which is >= n) * size of item, but even if 2n, still O(n)

- ### 링크드 리스트
    - [ ] Description:
        - [ ] [Singly Linked Lists (video)](https://www.coursera.org/learn/data-structures/lecture/kHhgK/singly-linked-lists)
        - [ ] [CS 61B - Linked Lists (video)](https://www.youtube.com/watch?v=sJtJOtXCW_M&list=PL-XXv-cvA_iAlnI-BQr9hjqADPBtujFJd&index=5)
    - [ ] [C Code (video)](https://www.youtube.com/watch?v=QN6FPiD0Gzo)
            - 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
    - [ ] Doubly-linked List
        - [Description (video)](https://www.coursera.org/learn/data-structures/lecture/jpGKD/doubly-linked-lists)
        - No need to implement

- ### 스택
    - [ ] [Stacks (video)](https://www.coursera.org/learn/data-structures/lecture/UdKzQ/stacks)
    - [ ] [Using Stacks Last-In First-Out (video)](https://archive.org/details/0102WhatYouShouldKnow/05_01-usingStacksForLast-inFirst-out.mp4)
    - [ ] Will not implement. Implementing with array is trivial.

- ### 큐
    - [ ] [Using Queues First-In First-Out(video)](https://archive.org/details/0102WhatYouShouldKnow/05_03-usingQueuesForFirst-inFirst-out.mp4)
    - [ ] [Queue (video)](https://www.coursera.org/learn/data-structures/lecture/EShpq/queue)
    - [ ] [Circular buffer/FIFO](https://en.wikipedia.org/wiki/Circular_buffer)
    - [ ] [Priority Queues (video)](https://archive.org/details/0102WhatYouShouldKnow/05_04-priorityQueuesAndDeques.mp4)
    - [ ] Implement using linked-list, with tail pointer:
        - enqueue(value) - adds value at position at tail
        - dequeue() - returns value and removes least recently added element (front)
        - empty()
    - [ ] Implement using fixed-sized array:
        - enqueue(value) - adds item at end of available storage
        - dequeue() - returns value and removes least recently added element
        - empty()
        - full()
    - [ ] Cost:
        - a bad implementation using linked list where you enqueue at head and dequeue at tail would be O(n)
            because you'd need the next to last element, causing a full traversal each dequeue
        - enqueue: O(1) (amortized, linked list and array [probing])
        - dequeue: O(1) (linked list and array)
        - empty: O(1) (linked list and array)

- ### 해쉬 테이블
    - [ ] Videos:
        - [ ] [Hashing with Chaining (video)](https://www.youtube.com/watch?v=0M_kIqhwbFo&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=8)
        - [ ] [Table Doubling, Karp-Rabin (video)](https://www.youtube.com/watch?v=BRO7mVIFt08&index=9&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
        - [ ] [Open Addressing, Cryptographic Hashing (video)](https://www.youtube.com/watch?v=rvdJDijO2Ro&index=10&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
        - [ ] [PyCon 2010: The Mighty Dictionary (video)](https://www.youtube.com/watch?v=C4Kc8xzcA68)
        - [ ] [(Advanced) Randomization: Universal & Perfect Hashing (video)](https://www.youtube.com/watch?v=z0lJ2k0sl1g&list=PLUl4u3cNGP6317WaSNfmCvGym2ucw3oGp&index=11)
        - [ ] [(Advanced) Perfect hashing (video)](https://www.youtube.com/watch?v=N0COwN14gt0&list=PL2B4EEwhKD-NbwZ4ezj7gyc_3yNrojKM9&index=4)

    - [ ] Online Courses:
        - [ ] [Understanding Hash Functions (video)](https://archive.org/details/0102WhatYouShouldKnow/06_02-understandingHashFunctions.mp4)
        - [ ] [Using Hash Tables (video)](https://archive.org/details/0102WhatYouShouldKnow/06_03-usingHashTables.mp4)
        - [ ] [Supporting Hashing (video)](https://archive.org/details/0102WhatYouShouldKnow/06_04-supportingHashing.mp4)
        - [ ] [Language Support Hash Tables (video)](https://archive.org/details/0102WhatYouShouldKnow/06_05-languageSupportForHashTables.mp4)
        - [ ] [Core Hash Tables (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/m7UuP/core-hash-tables)
        - [ ] [Data Structures (video)](https://www.coursera.org/learn/data-structures/home/week/3)
        - [ ] [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)
            - [Distributed Hash Tables (video)](https://www.coursera.org/learn/data-structures/lecture/tvH8H/distributed-hash-tables)

    - [ ] implement with array using linear probing
        - hash(k, m) - m is size of hash table
        - add(key, value) - if key already exists, update value
        - exists(key)
        - get(key)
        - remove(key)

## More Knowledge

- ### Binary search
    - [ ] [Binary Search (video)](https://www.youtube.com/watch?v=D5SrAga1pno)
    - [ ] [Binary Search (video)](https://www.khanacademy.org/computing/computer-science/algorithms/binary-search/a/binary-search)
    - [ ] [detail](https://www.topcoder.com/community/data-science/data-science-tutorials/binary-search/)
    - [ ] Implement:
        - binary search (on sorted array of integers)
        - binary search using recursion

- ### Bitwise operations
    - [ ] [Bits cheat sheet](https://github.com/jwasham/google-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: &, |, ^, ~, >>, <<
        - [ ] [words](https://en.wikipedia.org/wiki/Word_(computer_architecture))
        - [ ] Good intro:
            [Bit Manipulation (video)](https://www.youtube.com/watch?v=7jkIUgLC29I)
        - [ ] [C Programming Tutorial 2-10: Bitwise Operators (video)](https://www.youtube.com/watch?v=d0AwjSpNXR0)
        - [ ] [Bit Manipulation](https://en.wikipedia.org/wiki/Bit_manipulation)
        - [ ] [Bitwise Operation](https://en.wikipedia.org/wiki/Bitwise_operation)
        - [ ] [Bithacks](https://graphics.stanford.edu/~seander/bithacks.html)
        - [ ] [The Bit Twiddler](http://bits.stephan-brumme.com/)
        - [ ] [The Bit Twiddler Interactive](http://bits.stephan-brumme.com/interactive.html)
    - [ ] 2s and 1s complement
        - [Binary: Plusses & Minuses (Why We Use Two's Complement) (video)](https://www.youtube.com/watch?v=lKTsv6iVxV4)
        - [1s Complement](https://en.wikipedia.org/wiki/Ones%27_complement)
        - [2s Complement](https://en.wikipedia.org/wiki/Two%27s_complement)
    - [ ] count set bits
        - [4 ways to count bits in a byte (video)](https://youtu.be/Hzuzo9NJrlc)
        - [Count Bits](https://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetKernighan)
        - [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)
    - [ ] round to next power of 2:
        - [Round Up To Next Power Of Two](http://bits.stephan-brumme.com/roundUpToNextPowerOfTwo.html)
    - [ ] swap values:
        - [Swap](http://bits.stephan-brumme.com/swap.html)
    - [ ] absolute value:
        - [Absolute Integer](http://bits.stephan-brumme.com/absInteger.html)

## Trees

- ### Trees - Notes & Background
    - [ ] [Series: Core Trees (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/ovovP/core-trees)
    - [ ] [Series: Trees (video)](https://www.coursera.org/learn/data-structures/lecture/95qda/trees)
    - basic tree construction
    - traversal
    - manipulation algorithms
    - BFS (breadth-first search)
        - [MIT (video)](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13)
        - level order (BFS, using queue)
            time complexity: O(n)
            space complexity: best: O(1), worst: O(n/2)=O(n)
    - DFS (depth-first search)
        - [MIT (video)](https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14)
        - notes:
            time complexity: O(n)
            space complexity:
                best: O(log n) - avg. height of tree
                worst: O(n)
        - inorder (DFS: left, self, right)
        - postorder (DFS: left, right, self)
        - preorder (DFS: self, left, right)

- ### Binary search trees: BSTs
    - [ ] [Binary Search Tree Review (video)](https://www.youtube.com/watch?v=x6At0nzX92o&index=1&list=PLA5Lqm4uh9Bbq-E0ZnqTIa8LRaL77ica6)
    - [ ] [Series (video)](https://www.coursera.org/learn/data-structures-optimizing-performance/lecture/p82sw/core-introduction-to-binary-search-trees)
        - starts with symbol table and goes through BST applications
    - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/E7cXP/introduction)
    - [ ] [MIT (video)](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)
        - [ ] [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)
    - [ ] [Heap](https://en.wikipedia.org/wiki/Heap_(data_structure))
    - [ ] [Introduction (video)](https://www.coursera.org/learn/data-structures/lecture/2OpTs/introduction)
    - [ ] [Naive Implementations (video)](https://www.coursera.org/learn/data-structures/lecture/z3l9N/naive-implementations)
    - [ ] [Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/GRV2q/binary-trees)
    - [ ] [Tree Height Remark (video)](https://www.coursera.org/learn/data-structures/supplement/S5xxz/tree-height-remark)
    - [ ] [Basic Operations (video)](https://www.coursera.org/learn/data-structures/lecture/0g1dl/basic-operations)
    - [ ] [Complete Binary Trees (video)](https://www.coursera.org/learn/data-structures/lecture/gl5Ni/complete-binary-trees)
    - [ ] [Pseudocode (video)](https://www.coursera.org/learn/data-structures/lecture/HxQo9/pseudocode)
    - [ ] [Heap Sort - jumps to start (video)](https://youtu.be/odNJmw5TOEE?list=PLFDnELG9dpVxQCxuD-9BSy2E7BWY3t5Sm&t=3291)
    - [ ] [Heap Sort (video)](https://www.coursera.org/learn/data-structures/lecture/hSzMO/heap-sort)
    - [ ] [Building a heap (video)](https://www.coursera.org/learn/data-structures/lecture/dwrOS/building-a-heap)
    - [ ] [MIT: Heaps and Heap Sort (video)](https://www.youtube.com/watch?v=B7hVxCmfPtM&index=4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb)
    - [ ] [CS 61B Lecture 24: Priority Queues (video)](https://www.youtube.com/watch?v=yIUFT6AKBGE&index=24&list=PL4BBB74C7D2A1049C)
    - [ ] [Linear Time BuildHeap (max-heap)](https://www.youtube.com/watch?v=MiyLo8adrWw)
    - [ ] Implement a max-heap:
        - [ ] insert
        - [ ] sift_up - needed for insert
        - [ ] get_max - returns the max item, without removing it
        - [ ] get_size() - return number of elements stored
        - [ ] is_empty() - returns true if heap contains no elements
        - [ ] extract_max - returns the max item, removing it
        - [ ] sift_down - needed for extract_max
        - [ ] remove(i) - removes item at index x
        - [ ] heapify - create a heap from an array of elements, needed for heap_sort
        - [ ] heap_sort() - take an unsorted array and turn it into a sorted array in-place using a max heap
            - note: using a min heap instead would save operations, but double the space needed (cannot do 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)

- [ ] Implement:
    - [ ] 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)

## 그래프

그래프는 컴퓨터 과학의 여러 문제들을 표현하는 데 사용할 수 있다. 때문에 이 섹션은 트리나 정렬 섹션처럼 길다.

- 노트:
    - 메모리에 그래프를 표시하는 세 가지 기본 방법이 있다:
        - 오브젝트와 포인터
        - 행렬
        - 인접 리스트
    - 각각의 표현과 장단점을 숙지하라.
    - 넓이 우선 탐색(BFS)와 깊이 우선 탐색(DFS) - 계산상의 복잡성, 장단점, 실제 코드로 구현하는 방법을 알아야 한다.
    - 질문을 받을 시 먼저 그래프 기반 솔루션을 찾고, 없을 경우에 다른 솔루션으로 넘어가라.

- [ ] MIT(영상):
    - [ ] [너비 우선 탐색(BFS;Breadth-First Search)](https://www.youtube.com/watch?v=s-CYnVz-uh4&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=13)
    - [ ] [깊이 우선 탐색(DFS;Depth-First Search)]((https://www.youtube.com/watch?v=AfSk24UTFS8&list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb&index=14)

- [ ] Skiena의 강좌 - 시작하기 아주 좋습니다:
    - [ ] [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)

- [ ] 그래프 (검토, 그 외 여러가지):

    - [ ] [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://archive.org/details/ucberkeley_webcast_zFbq8vOZ_0k)
    - [ ] [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)

- 내가 구현할 것:
    - [ ] 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

Skiena의 책(아래의 책 섹션 참조)과 인터뷰 책에서 더 많은 그래프 실습을 할 수 있다.

## 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
    - **NOTE:** DP is a valuable technique, but it is not mentioned on any of the prep material Google provides. But you could get a problem where DP provides an optimal solution. So I'm including it.
    - 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
        - [ ] [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)
    - [ ] [Series of videos (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)

- ### 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
        - 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
    - These are Google papers and well-known 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.
    - [ ] [1978: Communicating Sequential Processes](http://spinroot.com/courses/summer/Papers/hoare_1978.pdf)
        - [implemented in Go](https://godoc.org/github.com/thomas11/csp)
        - [Love classic papers?](https://www.cs.cmu.edu/~crary/819-f09/)
    - [ ] [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: 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)
    - [ ] [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)

- ### 테스트
    - 알아 두어야 할 것:
        - 유닛 테스트는 어떻게 작동하는지
        - mock object 는 무엇인지
        - 통합 테스트는 무엇인지
        - 의존성 주입은 무엇인지
    - [ ] [James Bach과 함께하는 애자일 소프트웨어 테스트 (비디오)](https://www.youtube.com/watch?v=SAhJf36_u5U)
    - [ ] [소프트웨어 테스트에 대한 James Bach의 무료 강의 (비디오)](https://www.youtube.com/watch?v=ILkT_HV9DVU)
    - [ ] [Steve Freeman - Test-Driven 개발 (이것은 우리가 의미하는 것은 아니다) (비디오)](https://vimeo.com/83960706)
        - [참고자료](http://gotocon.com/dl/goto-berlin-2013/slides/SteveFreeman_TestDrivenDevelopmentThatsNotWhatWeMeant.pdf)
    - [ ] [TDD는 끝났다. 오래 사는 테스팅.](http://david.heinemeierhansson.com/2014/tdd-is-dead-long-live-testing.html)
    - [ ] [TDD는 정말 끝났는가? (비디오)](https://www.youtube.com/watch?v=z9quxZsLcfo)
    - [ ] [비디오 시리즈 (152 개) - 다 볼 필요 없음 (비디오)](https://www.youtube.com/watch?v=nzJapzxH_rE&list=PLAwxTw4SYaPkWVHeC_8aSIbSxE_NXI76g)
    - [ ] [파이턴과 함께하는 Test-Driven 웹 개발](http://www.obeythetestinggoat.com/pages/book.html#toc)
    - [ ] 의존성 주입:
        - [ ] [비디오](https://www.youtube.com/watch?v=IKD2-MAkXyQ)
        - [ ] [Tao Of Testing](http://jasonpolites.github.io/tao-of-testing/ch3-1.1.html)
    - [ ] [테스트 어떻게 작성하는지](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.coursera.org/learn/algorithms-part2/home/week/4)
        - [ ] [1. R Way Tries](https://www.coursera.org/learn/algorithms-part2/lecture/CPVdr/r-way-tries)
        - [ ] [2. Ternary Search Tries](https://www.coursera.org/learn/algorithms-part2/lecture/yQM8K/ternary-search-tries)
        - [ ] [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)](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 reliability engineer or operations 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 from Yegge:
    - 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/google-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/)

---

## 최종 검토

    이 섹션에는 중요한 개념들을 빠르게 검토할 수 있는 짧은 영상들이 포함되어 있다.
    복습을 하고자 한다면, 이 영상들이 도움이 될 것이다.

- [ ] 2-3분 분량의 주제별 짧은 영상 시리즈 (23 videos)
    - [Videos](https://www.youtube.com/watch?v=r4r1DZcx1cM&list=PLmVb1OknmNJuC5POdcDv5oCS7_OUkDgpj&index=22)
- [ ] 2-5분 분량의 주제별 짧은 영상 시리즈 - 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)

---

## 코딩 문제 연습

이제 당신은 위의 컴퓨터 과학 주제들을 모두 알고 있으므로, 코딩 문제에 답하는 것을 연습할 차례이다.

**코딩 문제 연습은 프로그래밍 문제에 대한 답을 외우는 것이 아니다.**

당신에게 프로그래밍 문제를 푸는 연습이 필요한 이유:
- 문제 인식, 그리고 어떤 자료구조와 알고리즘이 언제 필요한지
- 문제의 조건을 모으기
- 인터뷰를 하듯 당신이 문제를 푸는 과정을 말하기
- 컴퓨터가 아닌 종이나 화이트보드에 코딩하기
- 당신의 풀이의 시간, 공간 복잡도를 제시하기
- 당신의 해답을 테스팅하기


체계적이고 소통하는 인터뷰에서의 문제풀이에 관한 좋은 시작점이 있다. 당신은 프로그래밍 인터뷰 책에서 이 서식을 얻을 수도 있지만, 나는 이 것이 가장 좋다고 본다: [Algorithm design canvas](http://www.hiredintech.com/algorithm-design/)

[My Process for Coding Interview (Book) Exercises](https://googleyasheck.com/my-process-for-coding-interview-exercises/)

집에 화이트보드가 없는가? 그럴 수 있다. 나는 커다란 화이트보드를 가진 괴짜이다. 화이트보드 대신에 상점에서 큰 도화지를 사오자.
소파에 앉아서 연습할 수 있다. 이 것은 내 "소파 화이트보드"이다. 크기 비교를 위해 사진에 펜을 추가하였다. 펜을 쓰면, 곧 지우고 싶어질 것이다.
금방 지저분해 진다.

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

보충:

- [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)

**읽고 프로그래밍 문제 풀기 (순서대로):**

- [ ] [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

[위의 도서 목록](#book-list)을 보라

## 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/)

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)

Maybe:
- [Mock interviewers from big companies](http://www.gainlo.co/)

## 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

- [Ten Tips for a (Slightly) Less Awful Resume](http://steve-yegge.blogspot.co.uk/2007_09_01_archive.html)
- See Resume prep items in Cracking The Coding Interview and back of Programming Interviews Exposed


## 인터뷰가 다가오면 생각해보기

아래의 아이템들에 따른 너가 받을 20개의 인터뷰 질문에 대해 생각하라. 각각 2-3개의 대답을 준비해라.
당신이 성취한 것에 대해 데이터 뿐만 아니라 스토리를 만들어라.

- 왜 이 직업을 원합니까?
- 당신이 풀었던 문제중 힘들었던 문제는?
- 큰 도전에 직면한 적은?
- 최고의/최악의 디자인을 본적이 있는가?
- 현존하는 구글 제품들에 대해 향상시킬수 있는 아이디어
- 개인적으로 일할 때 가장 잘 일하는가? 아니면 팀원으로서 있을 때?
- 어떤 기술과 경험들이 당신의 역할에서 자산이 되었으며 그 이유는?
- 어떤 것이 가장 즐거웠는가 [job x / project y]?
- 무엇이 가장 큰 도전이었는가 [job x / project y]?
- 무엇이 가장 힘들었던 버그였는가? [job x / project y]?
- 무엇을 배웠는가 [job x / project y]?
- 무엇이 향상되었는가 [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!

- [10 things I wish I knew on my first day at Google](https://medium.com/@moonstorming/10-things-i-wish-i-knew-on-my-first-day-at-google-107581d87286#.livxn7clw)

Keep learning.

You're never really done.

---

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


    아래의 모든 것들은 선택 사항이다. 이 것들은 Google의 권장사항이 아니라, 나의 추천사항이다.
    당신은 이것들을 공부함으로써 더 많은 CS 개념들에 대해 알 수 있을 것이며, 소프트웨어 엔지니어링 직업을 준비하는 데에도 도움이 될 것
    이다. 더불어 당신은 훨씬 더 균형 잡힌 소프트웨어 엔지니어가 될 것이다.


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

---

## 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
- [ ] [Site Reliability Engineering](https://landing.google.com/sre/book.html)
    - [Site Reliability Engineering: How Google Runs Production Systems](https://landing.google.com/sre/)
- [ ] [UNIX and Linux System Administration Handbook, 4th Edition](https://www.amazon.com/UNIX-Linux-System-Administration-Handbook/dp/0131480057/)

## Additional Learning

- ### 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)

- ### 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.

- ### Emacs and vi(m)
    - suggested by Yegge, from an old Amazon recruiting post: 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
    - suggested by Yegge, from an old Amazon recruiting post. 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)

- ### 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)

- ### 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/)

- ### 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)

- ### 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)

- ### 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
    - 아래에 있는 영상을 확인하세요.

- ### 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)

## 영상 자료

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

- [온라인 CS 코스의 경로](https://github.com/open-source-society/computer-science)
- [CS 코스의 경로 (많은 온라인 강의가 포함되어 있는 경로)](https://github.com/prakhar1989/awesome-courses)

## 라이센스

[CC-BY-SA-4.0](./LICENSE.txt)