The Course is divided into 2 parts,

Part I : Introduction to CNNs

1. Introduction to Deep Learning and Computer Vision
2. Feed Forward Neural Networks
3. Introduction to CNNs
4. Optimization for training Deep neural networks
5. Deep Neural Networks
6. Tricks for Improving the Learning

Part II : Advanced Topics in Deep Learning

1. Introduction to DL packages/ Important architectures
2. Visualizing CNNs
3. Recurrent Neural Networks
4. Generative Modelling using Deep networks
5. Deep Reinforcement Learning
6. Invited Talks from Researchers in Industry.