Aban 99

Week Date Main Session Coursera Modules TA Session
1 17 - 23 Aban Introduction Study ML Basics if Needed (non-Coursera)
C1M1: Introduction to Deep Learning (2h)
Introduction to Colab, Numpy,
Visualization with Matplotlib, other libs
Pandas, Scikit-learn
2 24 - 30 Aban Introduction
slides (two sessions)
C1M2: Neural Networks Basics (8h) Tensorflow architecture
slides
Discussion about ML Basics, C1M1, First Assignment

Azar 99

Week Date Main Session Coursera Modules TA Session
3 1 - 7 Azar Deep Learning Intuition
slides
C1M3: Shallow Neural Networks (5h)
C1M4: Deep Neural Networks (5h)
Tensors, Basic operations in tensorflow
notebook
4 8 - 14 Azar Adversarial Attacks
Generative Adversarial Networks (GAN)
C2M1: Practical Aspects of Deep Learning (8h)
C2M2: Optimization Algorithms (5h)
Tensorflow model design APIs
slides
5 15 - 21 Azar Adversarial Attacks
Generative Adversarial Networks (GAN)
slides (two sessions)
C2M3: Hyperparameter Tuning, etc. (5h)
C3: ML Strategy (5h)
Tensorflow model training APIs
slides
6 22 - 28 Azar Project Proposal Presentation C4M1: Foundations of Convolutional Neural Networks (6h)
C4M2: Deep Convolutional Models: Case Studies (5h)
Project Proposal
Deadline: 21 Azar

Dey 99

Week Date Main Session Coursera Modules TA Session
7 29 Azar - 5 Dey Convolutional Neural Networks
slides
C4M3: Object Detection (4h)
C4M4: Special Applications: Face Recognition & Neural Style Transfer (5h)
CIFAR-10 Image classification example with tensorflow
notebook
8 6 - 12 Dey Transfer Learning
slides
C5M1: Recurrent Neural Networks (6h) Saving, restoring tensorflow models
slides
9 13 - 19 Dey Recurrent Neural Networks C5M2: Natural Language Processing & Word Embeddings (4h)
C5M3: Sequence Models & Attention Mechanism (5h)
TensorBoard
10 20 - 26 Dey Recurrent Neural Networks
slides (two sessions)
Introduction to Pytorch
slides
basics notebook
cifar-10 example

Bahman 99

Week Date Main Session Coursera Modules TA Session
11 27 Dey - 3 Bahman Interpretability of Neural Networks
slides
Progress Report: Dey 30th
12 4 - 10 Bahman Transformers
slides
Pytorch
13 11 - 18 Bahman Deep Reinforcement Learning HW Discussion


Final project report and presentation: 27 Bahman