UCB CS70 : discrete Math and probability theory
课程简介
- 所属大学：UC Berkeley
- 先修要求：无
- 编程语言：无
- 课程难度：🌟🌟🌟
- 预计学时：60 小时
伯克利的离散数学入门课程，个人觉得这门课最大的亮点在于并不是单纯的理论知识的讲授，而是在每个模块都会介绍理论知识在实际算法中的运用，让计算机系的学生在夯实理论基础的同时，跳脱出冰冷形式化的数学符号，在实际应用中感受和体会理论的本质。
具体的理论与算法的对应关系列举如下：
- 逻辑证明：稳定匹配算法
- 图论：网络拓扑设计
- 基础数论：RSA 算法
- 多项式环：纠错码设计
- 概率论：哈希表设计、负载均衡等等
课程 notes 也写得非常深入浅出，公式推导与实际例子星罗棋布，阅读体验很好。
课程资源
- 课程网站：http://www.eecs70.org/
- 课程教材：参见课程 notes
- 课程作业：参见课程 Schedule
资源汇总
@PKUFlyingPig 在学习这门课中用到的所有资源和作业实现都汇总在 PKUFlyingPig/UCB-CS70 - GitHub 中。
Last update: September 6, 2022
UCB CS70: Discrete Math and Probability Theory
Descriptions
- Offered by: UC Berkeley
- Prerequisites: None
- Programming Languages: None
- Difficulty: 🌟🌟🌟
- Class Hour: 60 hours
This is Berkeley's introductory discrete mathematics course. The biggest highlight of this course is that it not only teaches you theoretical knowledge, but also introduce the applications of theoretical knowledge in practical algorithms in each module. In this way, students majoring in CS can understand the essence of theoretical knowledge and use it in practice rather than struggle with cold formal mathematical symbols.
Specific theory-algorithm correspondences are listed below.
- Logic proof: stable matching algorithm
- Graph theory: network topology design
- Basic number theory: RSA algorithm
- Polynomial ring: error-correcting code design
- Probability theory: Hash table design, load balancing, etc.
The course notes are also written in a very in-depth manner, with derivations of formulas and practical examples, providing a good reading experience.
Course Resources
- Course Website: http://www.eecs70.org/
- Textbook: refer to course website
- Assignments: refer to course website
Personal Resources
All the resources and assignments used by @PKUFlyingPig in this course are maintained in PKUFlyingPig/UCB-CS70 - GitHub
Last update: September 24, 2022