Introductory Discrete Mathematics Pdf Github
I love MOOCs and MOOCs love me
MATH
Course | Institute | Rating | Type | Certificate | Note |
---|---|---|---|---|---|
Improving your statistical inferences | Eindhoven University of Technology | 4.9 | Statistical | ||
Matrix Algebra for Engineers | The Hong Kong University of Science and Technology | 4.5 | Linear Algebra | Blog Part1 Blog Part2 | |
Mathematical Thinking in Computer Science | UCSanDiego | Discrete Mathematics | |||
Mathematics for Machine Learning Specialization | Imperail London University | 4.5 | Math | ||
ARCHIVED Convex Optimization | Standford | Optimization | |||
Statistical Learning | Standford | Probability and Statistics | |||
Probability and Statistics | Standford | Probability and Statistics | |||
頑想學概率-機率一 | National Taiwan University | 4.8 | Probability and Statistics | ||
頑想學概率-機率二 | National Taiwan University | Probability and Statistics | |||
Mathematics for Computer Science | MIT | Math | |||
Basic Modeling for Discrete Optimization | The Chinese University of Hong Kong | 4.7 | Optimization | ||
Advanced Modeling for Discrete Optimization | The Chinese University of Hong Kong | Optimization | |||
Discrete Mathematics Generality | Pking University | 4.7 | Discrete Mathematics | ||
Methods and Statistics in Social Sciences | University of Amsterdam | Statistics | |||
Introduction to Discrete Mathematics for Computer Science | UCSanDiego | 4.5 | Discrete Mathematics | ||
Bayesian Statistics: From Concept to Data Analysis | UCSantaCruz | Statistics | |||
Introduction to Mathematical Thinking | Standford | Math | |||
18.06 Linear Algebra | MIT | Linear Algebra | |||
Calculus Applied | Harvard | Calculus | |||
Probability and Statistics in Data Science using Python | UCSanDiego | Probability and Statistics | |||
Introduction to Probability | Harvard | Probability and Statistics | |||
Calculus 1A: Differentiation | MIT | Calculus | |||
Calculus 1B: Integration | MIT | Calculus | |||
Calculus 1C: Coordinate Systems & Infinite Series | MIT | Calculus | |||
Linear Algebra - Foundations to Frontiers | UT Austin | Linear Algebra |
Computer Scicence
Course | Institute | Rating | Type | Certificate | Note |
---|---|---|---|---|---|
Programming Languages, Part A | UW | 4.9 | Programming Language | ||
Programming Languages, Part B | UW | 4.9 | Programming Language | ||
Programming Languages, Part C | UW | 4.9 | Programming Language | ||
Data Structures and Algorithms | UCSanDiego | 4.6 | Algorithm and Data Structure | ||
Algorithm Part1 | Priceton | 4.9 | Algorithm and Data Structure | ||
Algorithm Part2 | Priceton | 4.9 | Algorithm and Data Structure | ||
Nand to Tetris Part I | Hebrew University of Jerusalem | 5 | System | Github | |
Nand to Tetris Part II | Hebrew University of Jerusalem | 5 | System | ||
Algorithms Specialization | Standford | Algorithm and Data Structure | |||
An Introduction to Programming the Internet of Things (IOT) Specialization | University of California, Irvine | 4.6 | Hardware | ||
Functional Programming in Scala | École Polytechnique Fédérale de Lausanne | 4.5 | Programming Language | ||
C程序设计进阶 | Peking University | 4.8 | Programming Language | ||
Java Programming and Software Engineering Fundamentals Specialization | Duke | 4.5 | Programming Language | ||
Introduction to Programming with MATLAB | Vanderbilt University | 4.5 | Programming Language | ||
Analysis of Algorithms | Priceton | Algorithm and Data Structure | |||
Bitcoin and Cryptocurrency Technologies | Priceton | Bitcoin | |||
Computer Science: Algorithms, Theory, and Machines | Princeton University | System | |||
CS 61A: Structure and Interpretation of Computer Programs | UCBerkeley | System | |||
CS161: Algorithm | Standford | Algorithm and Data Structure | |||
Operating Systems Design and Implementation | Standford | Operating Systems | |||
Operating System Engineering | MIT | Operating Systems | |||
Introduction to Computer Systems (ICS) | CMU | Computer System | |||
6.006 Introduction to Algorithms | MIT | Algorithm and Data Structure | |||
Accelerated Computer Science Fundamentals | Coursera | Algorithm and Data Structure |
Machine Learning
Course | Institute | Rating | Type | Certificate | Note |
---|---|---|---|---|---|
Machine Learning Foundations | University of Washington | 4.7 | Machine Learning | See note in blog, ruochi.ai | |
Advanced Machine Learning Specialization | National Research University Higher School of Economics | 5.0 | Deep Learning | Github | |
Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization | 4.6 | Machine Learning | |||
Machine Learning | Standford | 5 | Machine Learning | Blog,Machine Learning | |
Deep Learning | deeplearning-ai | 5.0 | Deep Learning | Blog,Sequence Models Blog,Convolutional Neural Networks Blog, Neural Networks and Deep Learning Blog, Improving Deep Neural Networks Blog,Structuring Machine Learning Projects | |
Self-Driving Cars Specialization | University of Toronto | 5 | Self-Driving | ||
Self-Driving Cars Teach-Out | University of Michigan | 4.9 | Self-Driving | ||
機器學習基石上 | National Taiwan University | 4.9 | Machine Learning | ||
機器學習基石下 | National Taiwan University | 4.9 | Machine Learning | ||
Recommender Systems Specialization | University of Minnesota | Recommender Systems | |||
Probabilistic Graphical Models Specialization | Standford | 4.7 | Graphical Model | ||
CS224n: Natural Language Processing with Deep Learning | Stanford | Natural Language Processing | |||
CS224u: Natural Language Understanding | Stanford | Natural Language Processing | |||
CS231n: Convolutional Neural Networks for Visual Recognition | Standford | Computer Vision | |||
CS246: Mining Massive Data Sets | Standford | Big Data | |||
CS229: Machine Learning | Standford | Machine Learning | |||
CS236: Deep Generative Models | Standford | GAN | |||
CS234: Reinforcement Learning | Standford | Reinforcement Learning | |||
CS230 Deep Learning | Standford | Computer Vision | |||
CS285: Deep Reinforcement Learning | Standford | Computer Vision | |||
CS294-158 Deep Unsupervised Learning | Berkeley | Unsupervised Learning | |||
11-785 Introduction to Deep Learning | Standford | Deep Learning | |||
TensorFlow in Practice | deeplearning-ai | 4.3 | Deep Learning | ||
TensorFlow: Data and Deployment | deeplearning-ai | 4.3 | Deep Learning |
Big Data Architecture
Course | Institute | Rating | Type | Certificate | Note |
---|---|---|---|---|---|
Data Systems Specialization | ASU | 4.0 | Database | ||
Big Data Specialization | UCSD | 4.7 | Big Data | ||
Cloud Computing Specialization | UIUC | 4.4 | Cloud Computing | ||
CS199,Applied Cloud Computing | UIUC | 4.4 | Cloud Computing | ||
Parallel, Concurrent, and Distributed Programming in Java | Rice University | 4.5 | Programming Language | Github |
Artificial Intelligence
Course | Institute | Rating | Type | Certificate | Note |
---|---|---|---|---|---|
AI for Everyone | deeplearning-ai | 5 | Artificial Intelligence | Blog, AI for Everyone | |
AI-Sys Spring 2019 | berkeley | 5 | Artificial Intelligence | ||
CSE 599W | UW | 5 | AI system | ||
AI-Sys Spring 2019 | berkeley | 5 | Artificial Intelligence | ||
Artificial Intelligence | Berkeley | 5 | Artificial Intelligence | ||
AI for Medicine | deeplearning-ai | 4.7 | Artificial Intelligence |
Introductory Discrete Mathematics Pdf Github
Source: https://github.com/zhangruochi/Master-Computer-Science
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