The student can choose to attend all modules (Full School) or can select among different modules to build the personalized learning and training path based on her/his project, learning needs, and interests.
You can compute the cost of your personalised learning path through the Pre-enrollment form here.
| 🏫 MODULES | ⏳HOURS | 📖 COURSES | ⏳ HOURS | TEACHER | PROPAEDEUTICITIES | 
| FULL SCHOOL | 262 | ALL COURSES | 262 | All | – | 
| INTRODUCTION AND SEMINARS | 16 | Introduction to the School and AI | 4 | Baldassarre / Caligiore | No propadeuticity | 
| Job in the digital era | 4 | Morabito | |||
| Prosthetics and biomedical robotics | 4 | Zollo | |||
| Robotics for Elder Care | 2 | Fracasso | |||
| Collective Intelligence for Decision Support: Theory, Practice and Applications in Medical Diagnostics | 2 | Trianni | |||
| PYTHON PROGRAMMING AND DEPLOYMENT | 38 | Python, Basic programming tools (Anaconda, Colab) | 28 | Tamantini | No propadeuticity | 
| Application Versioning (github) and Deployment (docker, web app) | 10 | Moscatelli | |||
| MATHS 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 | Python programming and Deployment, Maths and programming 
 | 
| Numerical optimisation | 8 | Carli | |||
| Machine Learning | 28 | Merone | |||
| Elements of deep learning | 14 | Capirchio | |||
| MACHINE LEARNING ADVANCED | 70 | Deep Learning for computer vision | 12 | Capirchio | 
 
 
 Python programming and Deployment, Maths and programming, 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 | DePersis | |||
| Time series analysis, Transformers | 16 | Bacco / D’Antoni | |||
| Data augmentation | 4 | D’Amore | |||
| Large Language Models: prompting, RAG | 8 | Basile | |||
| Development and Deployment of LLM Web App | 6 | Gnocchi | |||
| BRAIN MODELLING | 34 | AI for system neuroscience | 4 | Baldassarre / Caligiore | 
 
 Python programming and Deployment, Maths and programming 
 | 
| Probabilistic computational models of brain | 12 | 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 | Final students test | 4 | Caligiore | 
 |