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Computer Science - Great Courses
This is a list of high-quality courses that, for one reason or another, didn't make it into the curriculum. The most common reasons are that the course isn't available often enough, or that there was an alternative that fit better into the curriculum.
Programming
Math
Courses | Duration | Effort |
---|---|---|
Effective Thinking Through Mathematics | 4 weeks | 2 hours/week |
Introduction to Mathematical Thinking | 10 weeks | 10 hours/week |
High School Math | - | - |
Precalculus | 5 weeks | 6 hours/week |
Advanced Precalculus | 4 weeks | 5 hours/week |
Calculus Applied! | 10 Weeks | 6hours/week |
Introduction to Probability and Data | - | - |
Linear Algebra (Strang) | - | - |
Introduction to Computational Thinking | - | - |
Multivariable Calculus | 13 weeks | 12 hours/week |
Introduction to Probability - The Science of Uncertainty | 18 weeks | 12 hours/week |
Matrix Methods In Data Analysis, Signal Processing, And Machine Learning | - | - |
Systems
Courses | Duration | Effort |
---|---|---|
Cloud Computing / Distributed Programming | 5 weeks | 5-10 hours/week |
Introduction to Parallel Programming (alt) (HW) | 12 weeks | 8-10 hours/week |
Intro to Computer Systems (Labs) | 15 weeks | 12 hours/week |
Great Ideas in Computer Architecture (Machine Structures) (Lectures) | 15 weeks | 12 hours/week |
Computer Architecture | - | 5-8 hours/week |
Operating System Engineering | - | - |
Introduction to Operating Systems | 8 weeks | 5-8 hours/week |
Advanced Operating Systems | 5 weeks | 5-8 hours/week |
Computer Networking | 12 weeks | 5-8 hours/week |
Distributed Systems - Playlist, Course site, Self-studying 6.824 6.824 Discord group for further help | - | - |
Theory
Courses | Duration | Effort |
---|---|---|
Algorithms, Part I | 6 weeks | 6-12 hours/week |
Algorithms, Part II | 6 weeks | 6-12 hours/week |
Analysis of Algorithms (Sedgewick) | 6 weeks | 6-8 hours/week |
Analysis of Algorithms (Skiena) | 15 weeks | 6-8 hours/week |
Programming Challenges (Skiena) | 14 weeks | 6-8 hours/week |
Data Structures and Algorithms (Specialization) | 25 weeks | 3-10 hours/week |
Algorithmic Thinking (Part 1) | - | - |
Algorithmic Thinking (Part 2) | - | - |
Statistical Mechanics: Algorithms and Computations | - | - |
Approximation Algorithms Part I | - | - |
Approximation Algorithms Part II | - | - |
Design And Analysis Of Algorithms | - | - |
Applications
Courses | Duration | Effort |
---|---|---|
Using Databases with Python | 5 weeks | 2-3 hours/week |
Database Systems | - | 27 hours |
Database Management Essentials | 7 weeks | 4-6 hours/week |
Intro to Artificial Intelligence | 16 weeks | 6-10 hours/week |
Intro to Machine Learning | 10 weeks | 6-10 hours/week |
Machine Learning for Data Science and Analytics | 5 weeks | 7-10 hours/week |
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center | 7 weeks | 4-5 hours/week |
Tools
Courses | Duration | Effort |
---|---|---|
How to Use Git and GitHub | 3 weeks | 2-3 hours/week |
Kubernetes Certified Application Developer | 5 weeks | 2 hours/week |
Online Learning - Great Courses
Courses | Duration | Effort |
---|---|---|
Learning How to Learn | 4 weeks | 2 hours/week |
Mindshift | 4 weeks | 2 hours/week |