Weekly Materials
Lectures, practice sessions, and assignments for each week
Part I: Foundations & Python
1
Sep 15
Introduction to ML
Machine Learning • Nuvolos Setup
2
Sep 22
No Class - Holiday
Swiss Federal Fast
3
Sep 29
Python Crash Course
Python • Jupyter • NumPy • SciPy • GitHub
4
Oct 6
Supervised Learning - Regression
Linear/Polynomial Regression • Gradient Descent
5
Oct 13
Generative AI & LLMs
Programming with AI • Autonomous Agents
6
Oct 20
Supervised Learning - Classification
k-NN • Naive Bayes • Decision Trees • Boosting
Part II: Deep Learning & Neural Networks
Part III: Advanced Topics
11
Nov 24
Dimensionality & Active Learning
Curse of Dimensionality • PCA • Active Subspaces
12
Dec 1
Unsupervised Learning
k-Means • GMM • EM • Hierarchical/DBSCAN
13
Dec 8
Reinforcement Learning
RL Intro • Q-Learning • Portfolio Optimization
14
Dec 15
Applications & Wrap-up
Deep Uncertainty Quantification • Projects