跟在CMU读CS的大学室友聊天,我说真羡慕可以听原书作者讲课,然后她给我分享了几个她觉得好的课的课件和Lab,并且可以去ytb或B站找到相应的视频。于是我做了一个简单的整理,持续更新。
 
Part I:Mathematics

1. 3Blue1Brown 线性代数的本质:https://www.bilibili.com/video/BV1ys411472E(官方双语,建议复制链接去浏览器打开,直接点击超链会显示视频消失不见了…不知道什么原因…)

2. MIT 18.06-Linear Algebra: https://open.163.com/newview/movie/courseintro?newurl=%2Fspecial%2Fopencourse%2Fdaishu.html (双语)配套习题: https://www.bilibili.com/video/BV19b411E7ue?from=search&seid=3345362936687764721

3. 3Blue1Brown 微积分的本质: https://www.bilibili.com/video/BV1qW411N7FU?from=search&seid=6943878902309957340 (官方双语)

4. MIT 6.041-Probabilistic Systems Analysis and Applied Probability: https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041sc-probabilistic-systems-analysis-and-applied-probability-fall-2013/ (官方无字幕) https://www.bilibili.com/video/BV1tt411C79s?from=search&seid=8833884752094582480 (双语搬运)

5. Crash Course Statistics: https://www.bilibili.com/video/BV1B7411v73M?from=search&seid=760545275776167522 (双语)

6. CMU 10-600-Math Background for ML: https://www.youtube.com/playlist?list=PL7y-1rk2cCsA339crwXMWUaBRuLBvPBCg (生肉,没找到PDF)
 
Part II:Computer Science

1. (神级)CMU 15213-Introduction to Computer Systems: https://scs.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID=%22b96d90ae-9871-4fae-91e2-b1627b43e25e%22&maxResults=150 (英语)  https://www.cs.cmu.edu/afs/cs/academic/class/15213-f15/www/schedule.html (官方)

2. UCB cs61b-Data Structures: https://inst.eecs.berkeley.edu/~cs61b/archives.html (官方英语+PDF),Lab和Project十分经典。

3. CMU 10601-Machine Learning: https://www.cs.cmu.edu/~ninamf/courses/601sp15/lectures.shtml (官方英语+PDF)

4. UW CSE341-Programming Languages: https://courses.cs.washington.edu/courses/cse341/16sp/  (官方英语) https://www.coursera.org/learn/programming-languages (Coursera版)

5. Android Programming: https://www.coursera.org/learn/android-programming (Coursera)

6. MIT The Missing Semester of Your CS Education: https://www.bilibili.com/video/BV1aE41157q6 (搬运双语) https://www.youtube.com/playlist?list=PLyzOV

7.  Applied Data Science with Python: https://www.coursera.org/specializations/data-science-python (Coursera)

8. CMU 15445-Database Systems: https://15445.courses.cs.cmu.edu/fall2018/schedule.html (官方英语+PDF)

Part III:Tools and Websites

1. UCB EECS 课程列表: https://inst.eecs.berkeley.edu//classes-eecs.html

2. MIT Courses: https://ocw.mit.edu/courses/

3. CMU: https://www.andrew.cmu.edu/courseweb/browse.shtml

4. Stanford: https://www.edx.org/ (神网)

5. 不知道哪来的网址可以看到很多CMU的课程: https://scs.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx#folderID=%22b96d90ae-9871-4fae-91e2-b1627b43e25e%22&maxResults=150

Part IV:Books

  1. SICP, 《Structure and Interpretation of Computer Programs》, 中文名是《计算机程序的构造和解释》,伯克利教授搞了一个教学网站,用python教SICP:http://composingprograms.com/
  2. Code Complete,《代码大全》
  3. Parsing Techniques(轮子哥推荐):https://book.douban.com/subject/4291903/
  4. 程序员的数学https://book.douban.com/subject/19949020/
  5. Effective Python
  6. Python Cookbook
  7. 附上一个仓库:https://github.com/imarvinle/awesome-cs-books

More:小窍门

1. 学校+课程号+年份搜索,若该年份找不到,可以换一个年份

2. 用课程号去搜B站,一般会有熟肉。去搜GitHub,一般会有大佬们Lab或Assignment的答案。