1. Linear Algebra & Statistics

2. Types of learning

3. Regression

4. Decision Tree

5. Dimensionality Reduction

6. Classification – Linear models

7. Hyperplane Classifiers – ANN, SVM

8. k-means Clustering

9. Deep Neural Networks – CNN, RNN, LSTM

10. Naive Bayes Classifier

11. Recommendation systems

12. Bagging and Boosting

13. Model selection and evaluation

14. Project

15. Online Examination

Total hours: 50