Each lecture has its associated readings listed under the link to the lecture material. Assignments and their scheduling is subject to change throughout the semester.
This class is split into three sections: Pythonic Foundations, Data Science, and Web Development.
| Week | Date | Topics | Homework |
|---|---|---|---|
| 0 | 08/31 | Python Basics | HW0 |
| 1 | 9/7 | Data Structures and Algorithms | |
| 2 | 9/14 | Pythonic Programming | HW1 |
| 3 | 9/21 | Exceptions, Modules and Files | |
| 4 | 9/28 | Machine Learning and Data Science with NumPy, Pandas, and Sci-Kit Learn | HW2 |
| 5 | 10/5 | Natural Language Processing with SpaCy | |
| 6 | 10/12 | Deep Learning with Keras/Tensorflow | HW3 |
| 7 | 10/19 | REST APIs with Flask | |
| 8 | 10/26 | Full Stack Development with Django | HW4 |
| 9 | 11/2 | Relational Databases and Security | |
| 10 | 11/9 | Cloud Computing with Docker | HW5 |
| 11 | 11/16 | Lightning Lectures [TBD] | |
| 12 | 11/23 | Course Wrap-Up | Final Project |
A variety of handy guides to quickly get yourself up and running:
| Topics | Resources |
|---|---|
| Installing Python | Guide |
| Development Environment | Guide |
| Unix Commands | Guide |
| Git Reference | Guide |