OUTLINE.txt

# ENEL 645 - Course Outline - Winter 2021

## Week 01 (Jan 10-16, 2021) Python Bootcamp and basic machine learning concepts 
- Introduction to Python 3 and Numerical Python (NumPy);
- Avoiding loops in Python to write efficient code;
- Historical context from machine learning to deep learning.;
- Basic machine learning concepts
	- Supervised and unsupervised learning;
	- Classification and regression;
	- Binary, multi-class, and multi-label classification;
	- Experimental design;
	- Overfitting and regularization through a polynomial fitting example; 

## Week 02 (Jan 17-23, 2021) Fully Connected Neural Networks 

## Week 03 (Jan 24 – Jan 30, 2021) Consolidating the knowledge

## Week 04 (Jan 31 – Feb 6, 2021) Convolutional Neural Networks (CNNs) and model fine-tuning 

## Week 05 (Feb 7 – Feb 13, 2021) Fully Convolutional Neural Networks 

## Week 06 (Feb 14 – Feb 20, 2021) Consolidating the knowledge

## Week 07 (Feb 21 – Feb 27, 2021) Recurrent Neural Networks 

## Week 08 (Feb 28 - Mar 6, 2021) Term break (i.e., reading week)

## Week 09 (Mar 7 - Mar 13, 2021) Generative Adversarial Networks 

## Week 10 (Mar 14 – Mar 20, 2021) Consolidating the knowledge 

## Week 11 (Mar 21 – Mar 27, 2021) Self-supervised learning

## Week 12 (Mar 28 - Apr 3 , 2021) Overview of recent trends in deep learning

## Week 13 (Apr 4 – Apr 10, 2021) Consolidating the knowledge

## Week 14 (Apr 11 – Apr 15, 2021) Teams final project reports and presentations are due