| Date |
Topic |
Readings / Videos |
Assignments |
| 08 Apr |
|
|
|
| 15 Apr |
Deep Neural Networks
|
|
Programming Assignment 1: Basic MLP
|
| 22 Apr |
Gradient Descent and Backpropagation
|
|
Programming Assignment 1.5: torch.nn
|
| 29 Apr |
Regularization
|
|
Programming Assignment 2: Visualizing the Training Process
|
| 06 May |
CNNs
|
|
Programming Assignment 3: Optimization & Regularization
|
| 13 May |
Advanced CNN Architectures
|
|
Programming Assignment 4: Probing CNNs
|
| 20 May |
Recurrent Neural Networks
|
|
Programming Assignment 5: Adversarial Examples
|
| 27 May |
Attention and Memory
|
|
Programming Assignment 6: Sequence Classification with RNNs
|
| 03 Jun |
Transformers and Language Models
|
|
|
| 10 Jun |
Graph Neural Networks
|
|
Programming Assignment 7: Basic Language Models
|
| 17 Jun |
Autoencoders and Self-Supervised Representation Learning
|
|
Programming Assignment 8: Graph Neural Networks
|
| 24 Jun |
Resource-Constrained Deep Learning
|
|
Programming Assignment 9: Self-Supervised Pretraining
|
| 01 Jul |
Introspection
|
|
Programming Assignment 10: Prototypical Networks
|
| 08 Jul |
Wrap-Up
|
|
Programming Assignment 11: Explaining Deep Neural Networks
|