1. Introduction to Deep Learning

2. Fundamentals of Deep Neural Networks

3. Training of Network: Backpropogation

4. Bias and Variance Tradeoff 

5. Fundamentals of CNN

6. Example of CNN

7. Variants of CNN

8. Recurrent Neural Network (RNN)

9. LSTM and Its Variants

10. Transformers

11. Autoencoders

12. Deep Learning Frameworks

First Test