(Tentative) Course Calendar

WEEK 01:

2025-02-24 Monday - Lecture 01: Course introduction & Motivation & Taxonomy of ML

2025-02-27 Thursday - Lecture 02: Introduction to Statistics for Machine Learning

2025-02-28 Friday - Lecture 03 (Lab 01): Introduction to Python

WEEK 02:

2025-03-01 Monday - Lecture 04: Data Visualization, GIT

2025-03-04 Thursday - Lecture 05: Principal Component Analysis 

2025-03-05 Friday - Lecture 06 (Lab 02): Elaborate and Visualize data

WEEK 03:

2025-03-10 Monday - Lecture 07: Supervised Learning, linear regression, training vs testing

2025-03-13 Thursday - Lecture 08: Overfitting and Ridge Regression, crossvalidation

2025-03-14 Friday - Lecture 09 (Lab 03): Linear Regression and Ridge Regression

WEEK 04:

2025-03-17 Monday - Lecture 10: Ridge Regression vs LASSO, gradient descent

2025-03-20 Thursday - Lecture 11: Classification, Logistic Regression

2025-03-21 Friday - Lecture 12 (Lab 04): Regularization & Classification

WEEK 05:

2025-03-24 Monday - Lecture 13: Multiclass Classification and Softmax Regression, Introduction to performance metrics: accuracy, precision, recall, F1-score / Handling unbalanced data

2025-03-27 Thursday - Lecture 14: Decision trees, overfitting and pruning

2025-03-28 Friday - Lecture 15 (Lab 05): Decision Trees 

WEEK 06:

2025-03-31 Monday - Lecture 16: Ensemble Methods: Bagging, Random Forests, bootstrap aggregating

2025-04-03 Thursday - Lecture 17: AdaBoost, XGBoost, Catboost

2025-04-04 Friday - Lecture 18 (Lab 06): Ensemble approaches

WEEK 07:

2025-03-17 Monday - Lecture 19: Support Vector Machines (SVM), Linear and kernel-based approaches, Concept of the margin and kernel trick

2025-04-10 Thursday - Lecture 20: Unsupervised Learning: K-Means Clustering. Evaluating clustering performance.

WEEK 08:

2025-04-14 Monday - Lecture 22: Anomaly Detection

2025-04-17 Thursday - Lecture 23: Introduction to Neural Networks, Activation functions (ReLU, sigmoid, softmax), Perceptrons

WEEK 09:

2025-04-24 Thursday - Lecture 24: Training of NN #01

WEEK 10:

2025-04-28 Monday - Lecture 25: Training of NN #02

WEEK 11:

2025-05-05 Monday - Lecture 26: CNN

2025-05-08 Thursday - Lecture 27: Autoencoders

2025-05-09 Friday - Lecture 28 (Lab 08): NN #01

WEEK 12:

2025-05-13 Monday - Lecture 29: RNN

2025-05-16 Friday - Lecture 30 (Lab 09): NN #02 

WEEK 13:

WEEK 14:

2025-05-26 Monday - Lecture 31: XAI #01

2025-05-29 Thursday - Lecture 32: XAI #02

2025-05-30 Friday - Lecture 33 (Lab 10): XAI

WEEK 15:

2025-06-05 Thursday - Lecture 34: Fairness in ML

2025-06-06 Friday - Lecture 35: Real-world Applications and MLOps

WEEK 16:

2025-06-09 Monday - Lecture 36: What’s next