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.
| Courses | Duration | Effort |
|---|---|---|
| Introduction to Computational Thinking and Data Science | 10 weeks | 15 hours/week |
| Introduction to Computer Science (Udacity) | 7 weeks | 10-20 hours/week |
| An Introduction to Interactive Programming in Python (Part 1) | 5 weeks | - |
| An Introduction to Interactive Programming in Python (Part 2) | - | - |
| Programming Basics | 9 weeks | 8 hours/week |
| Object-Oriented Programming | 4 weeks | 8 hours/week |
| Introduction to Programming with MATLAB | - | - |
| Introduction to Functional Programming | 7 weeks | 4-6 hours/week |
| The Structure and Interpretation of Computer Programs | - | - |
| Introduction to Haskell | 14 weeks | 4 hours/week |
| Courses | Duration | Effort |
|---|---|---|
| Effective Thinking Through Mathematics | 4 weeks | 2 hours/week |
| Introduction to Probability and Data | - | - |
| Linear Algebra (Strang) | - | - |
| Courses | Duration | Effort |
|---|---|---|
| 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 |
| 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 | - | - |
| 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 |
| Processing Big Data with Azure HDInsight | 5 weeks | 3-4 hours/week |
| Big Data Science with the BD2K-LINCS Data Coordination and Integration Center | 7 weeks | 4-5 hours/week |
| Courses | Duration | Effort |
|---|---|---|
| Learning How to Learn | 4 weeks | 2 hours/week |
| Mindshift | 4 weeks | 2 hours/week |