All Courses

AS-AI aims to train the next generation of interdisciplinary researchers, professionals and leaders to address their challenging problems by applying the powerful means of computational modelling.

AS-AI students come to the School with diverse academic and professional backgrounds (ICT, engineering, psychology, economics, social sciences, biology, health, humanities) and are stimulated to pioneer innovative, interdisciplinary approaches to yield new insights and finding innovative solutions in the field of interest.

This unique program is designed to be in-depth yet flexible: students are offered fundamental courses, specialistic courses, focussed courses, seminars and activities, with the aim to provide both a deep knowledge and specialisation and a broad view and transversal competences, skills and perspectives. The student can choose to attend all modules (Full School), alternatively, the student can select among different modules to build the personalized learning and training path based on her/his project, learning needs, and interests with the support of the School President, Director and of School Advisors. You could compute the cost of you personalised learning path through the Pre-enrollment form here.

At the end of the AS-AI, it is possible to be selected for an advanced project, which may lead to a publication and open the way to a possible PhD.

TITLE MODULES HOURS TITLE COURSES HOURS TEACHER PROPAEDEUTICITIES
FULL SCHOOL 254 ALL COURSES 254 ALL
INTRODUCTION AND SEMINARS 14 Introduction to the School and AI 4 Baldassarre – Caligiore No propaedeuticity
Job in the digital era 4 Morabito
Prosthetics and biomedical robotics 4 Zollo
Robotics for Elder Care 2 Cortellessa – Fracasso
PYTHON PROGRAMMING AND DEPLOYMENT 38 Python, Basic programming tools (Anaconda, Colab) 28 Tamantini No propaedeuticity
Application Versioning (github) and Deployment (docker, web app) 10 Moscatelli
MATH AND PROGRAMMING 30 Maths for AI 12 Baldassarre No propaedeuticity
Linear Algebra for AI with Python 10 Caligiore
Basic statistic for AI 4 Capirchio
Probability theory for AI 4 Cartoni
MACHINE LEARNING BASICS 58 Big data analysis with Pandas 8 Cecconi MATH AND PROGRAMMING, PYTHON PROGRAMMING AND DEPLOYMENT
Numerical optimisation 8 Battiloro
Machine Learning 28 Merone
Elements of deep learning 14 Capirchio
MACHINE LEARNING ADVANCED 68 Deep Learning for computer vision 12 Capirchio MATH AND PROGRAMMING, PYTHON PROGRAMMING AND DEPLOYMENT,MACHINE LEARNING BASICS
AI Lab: ML vs deep network for motion perception
4 Tamantini
Natural Language Processing 12 Reforgiato
AI Lab: Deep networks for NLP
8 De Persiis
Time series analysis, Transformers 16 Bacco-D’Antoni
Data augmentation 4 D’Amore
Large Language Models: prompting, RAG 8 Basile
Deployment of AI Web App (on promise and cloud examples)
4 Gnocchi
BRAIN MODELLING 30 AI for system neuroscience 4 Baldassarre-Caligiore MATH AND PROGRAMMING,PYTHON PROGRAMMING AND DEPLOYMENT
Probabilistic computational models of brain 8 Cartoni
Firing-rate computational models of brain 12 Baldassarre
Modelling brain disorders through differential equations
6 Caligiore
ETHICAL AND LEGAL ASPECTS OF AI 12 AI impact: individual, social, and technological anchors when everything changes 8 Baldassarre No propaedeuticity
EU and national AI legislation 4 Fasano
Student assessment 4 AI Lab: Final students test 4 Caligiore MATH AND PROGRAMMING,PYTHON PROGRAMMING AND DEPLOYMENT, MACHINE LEARNING BASICS