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Machine Learning and Artificial Intelligence Lab

Professor: Riccardo Zecchina

Course description

Advances in Artificial Intelligence (AI) are having an ever-increasing impact in many areas of human life, from science and technology, to economics and medicine. Much more is coming, and to get a proper view of what we can expect in the next years, some clarity is needed. Artificial intelligence, Machine Learning, consists of a set of computational methods that automatically extract information from data through learning processes. The applications and developments of artificial intelligence therefore cover all aspects of human activities in which data play a role, at 360 degrees. In particular, AI should be thought of as a new investigative tool that complements and enhances traditional methods, and will bring widespread innovation.
AI has yet to enter its peak expansion phase. There exist pressing open problems which will lead to applications not yet thought of.

Objectives

Scope of the course is to provide an introduction to the fundamental concepts and tools of modern Artificial Intelligence and Machine Learning. These tools are at the root of data science, which are among the main pillars of modern science

a. The high dimensional nature of data
b. Supervised and unsupervised machine learning
c. Artificial Neural Networks: models and examples
d. Overview of applications


Suggested bibliography

Handouts and reading material will be provided.


The course is an introduction to our university’s interactive and hands-on approach to teaching the BSc in Mathematical and Computing Sciences for Artificial Intelligence.


Last modified 27/04/2021 - 12:40:57