Course Schedule

Here’s the schedule for the course.

  • The deadlines for handing in homeworks will be announced each session.
  • The deadline for the first progress report of the final project is 30 Farvardin, 1404
  • The deadline for the second progress report of the final project is 20 Khordad, 1404 (To be confirmed)
Week Date Lecture Lab Session
1 20 - 26 Bahman Course Introduction Introduction to Google Colab and Datasets/Problems for Homework
2 27 Bahman - 4 Esfand Data Cleaning and Preprocessing EDA/Cleaning in Action
3 5 - 11 Esfand Data Visualization Visualization Notebook + Web Scraping Notebook
2 12 - 18 Esfand Feature Engineering and Dimensionality Reduction Feature Engineering Notebook
3 19 - 25 Esfand Different Problem Types and Accuracy Measures Accuracy Measures and Scikit-learn
4 26 - 28 Esfand Regression Methods Regression Methods Notebook
5 17 - 23 Farvardin Classification Methods Classification Methods Notebook
6 24 - 30 Farvardin Multiclass/Multilabel Classification and Boosting Multiclass Classification and Boosting Notebook
7 31 Farvardin - 6 Ordibehesht Neural Networks Neural Networks Notebook
8 7 - 13 Ordibehesht Deep Learning Deep Learning Notebook
10 14 - 20 Ordibehesht Deep Learning Application: Image Classification Convolutional Neural Networks Notebook
11 21 - 27 Ordibehesht Generative AI GenAI Notebook
12 28 Ordibehesht - 3 Khordad Model Explainability and Imbalanced Data Problem Explainable AI and Imbalanced Data Problem
13 2 Khordad Guest Speakers from Inudstry  
14 4 - 10 Khordad Practical Stuff Practical Stuff Notebook
15 20 and 25 Khordad Final Projects Presentation Final Projects Presentation
16 ? Final Exam