This is a curated list of free courses from reputable universities like MIT, Stanford, and Princeton that satisfy the same requirements as an undergraduate Computer Science degree, minus general education.
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Intro to Computer Science | Harvard | 10 weeks | 10-20 hours/week | self-paced | none |
| Mathematical Thinking in Computer Science | UC San Diego | 6 weeks | 2-5 hours/week | once a month | none |
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Programming for Everybody (Getting Started with Python) | University of Michigan | 4 weeks | 4-6 hours/week | self-paced | none |
| Python Data Structures | University of Michigan | 4 weeks | 4-6 hours/week | self-paced | Programming for Everybody (Getting Started with Python) |
| Using Python to Access Web Data | University of Michigan | 4 weeks | 4-6 hours/week | self-paced | Python Data Structures |
| Using Databases with Python | University of Michigan | 3 weeks | 4-8 hours/week | self-paced | Using Python to Access Web Data |
| Capstone: Retrieving, Processing, and Visualizing Data with Python | University of Michigan | 2 weeks | 4-6 hours/week | self-paced | Using Databases with Python |
Alternative: Python 3 Programming Specialization | University of Michigan | 5 months | 7 hours/week | self-paced | none
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Calculus 1A: Differentiation | MIT | 12 weeks | 6-10 hours/week | self-paced | pre-calculus |
| Calculus 1B: Integration | MIT | 15 weeks | 6-10 hours/week | self-paced | Calculus 1A: Differentiation |
| Calculus 1C: Coordinate Systems & Infinite Series | MIT | 8 weeks | 6-10 hours/week | self-paced | Calculus 1B: Integration |
| Linear Algebra - Foundations to Frontiers | UT Austin | 15 weeks | 6-10 hours/week | self-paced | pre-calculus |
| Introduction to Probability and Data | Duke | 5 weeks | 5-7 hours/week | twice a month | none |
| Intro to Statistics | Udacity | 8 weeks | 5-7 hours/week | self-paced | none |
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Introduction to Data Science in Python | University of Michigan | 3 weeks | 4-6 hours/week | self-paced | basic programming knowledge |
| Applied Plotting, Charting & Data Representation in Python | University of Michigan | 4 weeks | 5-7 hours/week | self-paced | Introduction to Data Science in Python |
| Applied Machine Learning in Python | University of Michigan | 6 weeks | 5-7 hours/week | self-paced | Applied Plotting, Charting & Data Representation in Python |
| Applied Text Mining in Python | University of Michigan | 5 weeks | 5-7 hours/week | self-paced | Applied Machine Learning in Python |
| Applied Social Network Analysis in Python | University of Michigan | 5 weeks | 5-7 hours/week | self-paced | Applied Text Mining in Python |
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Build a Modern Computer from First Principles: From Nand to Tetris | Hebrew University of Jerusalem | 6 weeks | 5 hours/week | twice a month | basic programming knowledge |
| Build a Modern Computer from First Principles: From Nand to Tetris II | Hebrew University of Jerusalem | 6 weeks | 10-15 hours/week | once a month | Build a Modern Computer from First Principles: From Nand to Tetris |
| Introduction to Operating Systems | Georgia Tech | 8 weeks | 5-8 hours/week | self-paced | Build a Modern Computer from First Principles: From Nand to Tetris II |
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Computer Science: Algorithms, Theory, and Machines | Princeton | 10 weeks | 2-5 hours/week | once a month | Calculus 1A (all), basic programming |
| Algorithms, Part I | Princeton | 6 weeks | 6-12 hours/week | once a month | Computer Science: Algorithms, Theory, and Machines |
| Algorithms, Part II | Princeton | 6 weeks | 6-12 hours/week | once a month | Algorithms, Part I |
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Machine Learning | Stanford | 11 weeks | 5-7 hours/week | twice a month | Linear Algebra - Foundations to Frontiers |
| Database Management Essentials | CU | 7 weeks | 4-6 hours/week | twice a month | basic programming & CS knowledge |
| Cryptography I | Stanford | 7 weeks | 5 hours/week | once a month | Linear Algebra - Foundations to Frontiers & Introduction to Probability and Data |
| Courses | School | Duration | Effort | Frequency | Prerequisites |
|---|---|---|---|---|---|
| Linux Command Line Basics | Udacity | 1 week | 5 hours/week | self-paced | none |
| The Unix Workbench | JHU | 4 weeks | 4 hours/week | once a month | none |