Data Science Foundations¶
Welcome to Data Science Foundations, my name is Wesley
Visit the github repo to access all materials and code for this class
This is part II of a multi-part lesson path. Checkout Python Foundations for part I and General Applications of Neural Networks for part III
Access the solutions if you get stuck
The recommended schedule for this material:
| Day (2.5 hrs/day) | Modules |
|---|---|
| 1 | Session 1: Regression and Analysis Lab 1: Descriptive Statistics Data Hunt |
| 2 | Session 2: Inferential Statistics Lab 2: Inferential Statistics Data Hunt |
| 3 | Session 3: Model Selection and Validation Project Part 1: Statistical Analysis of Tic-Tac-Toe |
| 4 | Session 4: Feature Engineering Lab 3: Practice with Feature Engineering |
| 5 | Session 5: Unsupervised Learning Project Part 2: Heuristical Tic-Tac-Toe Agents |
| 6 | Session 6: Bagging Lab 4: Practice with Supervised Learners |
| 7 | Session 7: Boosting Lab 5: Practice with Writing Unit Tests Project Part 3: 1-Step Look Ahead Agents |
| 8 | Project Part 4: N-Step Look Ahead Agents |
Happy learning 🧑🏫