1. Introduction to Machine Learning

2. Supervised Learning: Regression

3. Supervised Learning: Classification

4. Underfitting and Overfitting

Live Session 13-11

5. Preprocessing Data: Cleaning, Encoding, Splitting

6. Evaluation Metrics

7. Practice Project

8. Research and Data Gathering

Live Session 11-12

9. Unsupervised Learning: Clustering - Universities

10. Pipelines - Uiversities

11. Mutual Information - Universities

12. Feature engineering - Universities