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计算机自学指南 - 新手入门教程
计算机自学指南 - 新手入门教程
语言：中文 | 章节：126 | 阅读：19193 | 收藏：3 | 评论：0
计算机自学指南 - 新手入门教程
计算机
自学
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一个仅供参考的 CS 学习规划
Stanford CS142: Web Applications
University of Helsinki: Full Stack open 2022
MIT Web Development Crash Course
前言
CS188: Introduction to Artificial Intelligence
CS50’s Introduction to AI with Python
智能计算系统
CS61C: Great Ideas in Computer Architecture
CMU CS15213: CSAPP
Digital Design and Computer Architecture
Coursera: Nand2Tetris
如何使用这本书
后记
好书推荐
CMU 15-418/Stanford CS149: Parallel Computing
MIT6.824: Distributed System
CMake
Docker
GNU Make
Git
GitHub
LaTeX
Scoop
Vim
毕业论文
底层核心逻辑
CS162: Operating System - 操作系统
MIT 6.S081: 操作系统工程 - 操作系统
NJU OS: 操作系统设计与实现
MIT18.06: 线性代数 - 数学基础
MIT Calculus Course
MIT Calculus Course
MIT6.050J: Information theory and Entropy
MIT6.050J: Information theory and Entropy
MIT 6.042J: Mathematics for Computer Science
MIT 6.042J: Mathematics for Computer Science
UCB CS126 : Probability theory
UCB CS126 : Probability theory
UCB CS70: Discrete Math and Probability Theory
UCB CS70 : discrete Math and probability theory
The Information Theory, Patter Recognition, and Neural Networks
The Information Theory, Patter Recognition, and Neural Networks
Stanford EE364A: Convex Optimization
Stanford EE364A: Convex Optimization
MIT18.330 : Introduction to numerical analysis
MIT18.330 : Introduction to numerical analysis
CMU 15-445: Database Systems
CMU 15-445: Database Systems
Caltech CS 122: Database System Implementation
UCB CS186: Introduction to Database System
UCB CS186: Introduction to Database System
Stanford CS 346: Database System Implementation
UCB Data100: Principles and Techniques of Data Science
UCB Data100: Principles and Techniques of Data Science
Coursera: Algorithms I & II
Coursera: Algorithms I & II
CS170: Efficient Algorithms and Intractable Problems
CS170: Efficient Algorithms and Intractable Problems
CS61B: Data Structures and Algorithms
CS61B: Data Structures and Algorithms
CS189: Introduction to Machine Learning
CS189: Introduction to Machine Learning
CS229: Machine Learning
Coursera: Machine Learning
Coursera: Machine Learning
CMU 10-414⁄714: Deep Learning Systems
Machine Learning Compilation
CMU 10-708: Probabilistic Graphical Models
STATS214 / CS229M: Machine Learning Theory
STA 4273 Winter 2021: Minimizing Expectations
Columbia STAT 8201: Deep Generative Models
机器学习进阶
CS224n: Natural Language Processing
CS224w: Machine Learning with Graphs
Coursera: Deep Learning
Coursera: Deep Learning
CS231n: CNN for Visual Recognition
CS285: Deep Reinforcement Learning
国立台湾大学：李宏毅机器学习
UCB EE16A&B: Designing Information Devices and Systems I&II
UCB EE16A&B: Designing Information Devices and Systems I&II
MIT 6.007 Signals and Systems
MIT 6.007 Signals and Systems
UCB EE120: Signal and Systems
UCB EE120: Signal and Systems
UCB CS161: Computer Security
UCB CS161: Computer Security
MIT 6.858: Computer System Security
MIT 6.858: Computer System Security
Amirkabir University of Technology 1400-2: Advanced Programming Course
Stanford CS106B/X: Programming Abstractions in C++
Stanford CS106B/X: Programming Abstractions in C++
CS106L: Stanford C++ Programming
CS106L: Standard C++ Programming
CS110L: Safety in Systems Programming
CS110L: Safety in Systems Programming
CS50: This is CS50x
CS50: This is CS50x
CS61A: Structure and Interpretation of Computer Programs
CS61A: Structure and Interpretation of Computer Programs
Introductory C Programming Specialization
Introductory C Programming Specialization
MIT: The Missing Semester of Your CS Education
MIT-Missing-Semester
Stanford CS143: Compilers
Stanford CS143: Compilers
CMU 15-462 : COMPUTER GRAPHICS
CMU 15-462 : COMPUTER GRAPHICS
Stanford CS148
GAMES101
GAMES103
GAMES202
CS144: Computer Network
CS144: Computer Network
Computer Networking: A Top-Down Approach
Computer Networking: A Top-Down Approach
USTC Computer Networking:A Top-Down Approach
USTC Computer Networking:A Top-Down Approach
MIT 6.031: Software Construction
MIT 6.031: Software Construction
UCB CS169: software engineering
UCB CS169: software engineering
善良比聪明更重要（评论内容审核后才会显示）
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