CS自学指南
培养方案Pro
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cs-self-learning
CS自学指南
cs-self-learning
前言
一个仅供参考的CS学习规划
必学工具
必学工具
翻墙
Vim
Git
GitHub
GNU Make
CMake
LaTeX
Docker
实用工具箱
毕业论文
好书推荐
数学基础
数学基础
MIT18.01/18.02: Calculus
MIT18.06: Linear Algebra
MIT6.050J: Information theory and Entropy
数学进阶
数学进阶
UCB CS70: discrete Math and probability theory
UCB CS126: probability theory
MIT 6.042J: Mathematics for Computer Science
MIT18.330: Introduction to numerical analysis
Standford EE364A: Convex Optimization
The Information Theory, Patter Recognition, and Neural Networks
编程入门
编程入门
MIT-Missing-Semester
Harvard CS50: This is CS50x
UCB CS61A: Structure and Interpretation of Computer Programs
Duke University: Introductory C Programming Specialization
Stanford CS106B/X
Stanford CS106L: Standard C++ Programming
Stanford CS110L: Safety in Systems Programming
电子基础
电子基础
EE16A&B: Designing Information Devices and Systems I&II
UCB EE120 : Signal and Systems
MIT 6.007 Signals and Systems
数据结构与算法
数据结构与算法
UCB CS61B: Data Structures and Algorithms
Coursera: Algorithms I & II
UCB CS170: Efficient Algorithms and Intractable Problems
软件工程
软件工程
MIT 6.031: Software Construction
UCB CS169: software engineering
体系结构
体系结构
Coursera: Nand2Tetris
Digital Design and Computer Architecture
UCB CS61C: Great Ideas in Computer Architecture
CMU 15-213: CSAPP
操作系统
操作系统
MIT 6.S081: Operating System Engineering
UCB CS162: Operating System
NJU OS: Operating System Design and Implementation
并行与分布式系统
并行与分布式系统
CMU 15-418/Stanford CS149: Parallel Computing
MIT 6.824: Distributed System
计算机系统安全
计算机系统安全
UCB CS161: Computer Security
MIT 6.858: Computer System Security
计算机网络
计算机网络
USTC Computer Networking:A Top-Down Approach
Computer Networking: A Top-Down Approach
Stanford CS144: Computer Network
数据库系统
数据库系统
UCB CS186: Introduction to Database System
CMU 15-445: Database Systems
Caltech CS122: Database System Implementation
编译原理
编译原理
Stanford CS143: Compilers
计算机图形学
计算机图形学
GAMES101
GAMES202
GAMES103
Stanford CS148
Web开发
Web开发
MIT web development course
Stanford CS142: Web Applications
数据科学
数据科学
UCB Data100: Principles and Techniques of Data Science
人工智能
人工智能
Harvard CS50's Introduction to AI with Python
UCB CS188: Introduction to Artificial Intelligence
智能计算系统
机器学习
机器学习
Coursera: Machine Learning
Stanford CS229: Machine Learning
UCB CS189: Introduction to Machine Learning
深度学习
深度学习
Coursera: Deep Learning
国立台湾大学：李宏毅机器学习
Stanford CS231n: CNN for Visual Recognition
Stanford CS224n: Natural Language Processing
Stanford CS224w: Machine Learning with Graphs
UCB CS285: Deep Reinforcement Learning
机器学习进阶
机器学习进阶
进阶路线图
CMU 10-708: Probabilistic Graphical Models
Columbia STAT 8201: Deep Generative Models
U Toronto STA 4273 Winter 2021: Minimizing Expectations
Stanford STATS214 / CS229M: Machine Learning Theory
后记
培养方案Pro
under construction.
最后更新:
November 30, 2021
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