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GTx CS1301, "Computing In Python" is proposed as a supplemental course in the OSSU curriculum and as a potential future candidate for the Introduction to Computer Science course. It is an online-adapted version of the on-campus Introduction to Computing course for Georgia Tech computer science students. The online version is comprised of four parts, delivered on-demand via edX. The course is self-paced with 16 weeks of effort, and is 100% free to audit with all materials included. It covers all introductory CS topics discussed in MIT 6.00.1x from a language-agnostic perspective, while providing additional instruction and support in learning Python as a language. Students who complete this course will have an understanding of basic CS topics **and** a working knowledge of Python 3 they can immediately apply to interesting problems.
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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 |
| Introduction to Probability and Data | - | - |
| Linear Algebra (Strang) | - | - |
Systems
| 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 |
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 | - | - |
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 |
| 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 |
Online Learning - Great Courses
| Courses | Duration | Effort |
|---|---|---|
| Learning How to Learn | 4 weeks | 2 hours/week |
| Mindshift | 4 weeks | 2 hours/week |