Summary
- Compulsory Module 4: Digital Technologies for Social Innovation
- Semester: II
- ECTS: 12
The Course consists of:
- Compulsory Module 4a (CM4a): Artificial Intelligence and Machine Learning (6 ECTS)
- Compulsory Module 4b (CM4b): Statistics and Data Science (6 ECTS)
The course examines the fundamentals in statistical methods, focusing in particular on statistical modeling using supervised and unsupervised learning. More specifically, through lectures and exercises, the course will address the following key topics:
- Artificial Intelligence and Machine Learning: Supervised learning: classification and regression. Unsupervised learning: clustering, density estimation, and dimensionality reduction. Reinforcement learning, Generative AI.
- Fundamentals in statistical methods: Statistical modeling using supervised and unsupervised learning. Multivariate analysis, cluster analysis. Independence tests. Linear models. Generalized linear models (GLMs).
Taught in English and offered on a biennial basis, the course combines theoretical insights with applied learning, preparing students to engage constructively in debates and practices at the intersection of societal challenges, digitalisation, statistics, data science, artificail intelligence and machine learning.