1. Introduction to Decision Tree
  2. Introduction to Eensembling Methods
  3. Introduction to Clustering
  4. Introduction to Feature Engineering
  5. Introduction to ML Pipeline & Model Tuning
  6. Recommender Systems
  7. Introduction to Neural Networks