Artificial Intelligence & Machine Learning

Artificial intelligence is the engine of innovation: this curriculum prepares you to play a leading role in the technological revolution, turning ideas into intelligent solutions for industry and research.

Download the AI&ML Curriculum Brochure [Italian only]

Scientific and Industrial Context

The integration of automated reasoning and machine learning represents one of the most promising areas in the development of artificial intelligence. In recent years, advances in these fields have transformed key sectors such as robotics, medical diagnostics, finance, and natural language processing. Machine learning techniques have proven extremely effective in solving complex problems based on large amounts of data, while automated reasoning—which includes formal logic and symbolic systems—provides mechanisms for structured information understanding and decision-making in uncertain environments. The combination of these two approaches is crucial for tackling future challenges, such as creating intelligent systems capable of interpreting context, adapting to changing situations, and learning autonomously. This has a significant impact on fields such as autonomous driving, industrial automation, and the development of advanced virtual assistants, requiring professionals capable of designing and optimizing systems that effectively combine learning and reasoning.

Educational Objectives

This study path aims to provide advanced training in the field of artificial intelligence, with a particular focus on automated reasoning and machine learning. Students will acquire a solid theoretical foundation in major machine learning models and logical reasoning techniques, learning to integrate these approaches to address complex problems in real-world contexts. The programme will provide tools for developing systems capable of learning from data, recognizing patterns, and making decisions based on logical rules and inferences. Topics such as optimization, modeling of complex systems, and managing uncertain environments will also be covered, with an application-oriented approach involving the implementation of advanced algorithms and the development of practical solutions. Upon completion, students will be able to design and optimize intelligent systems in fields such as automation, robotics, finance, and healthcare, combining theoretical and practical skills to create innovative and scalable solutions.

Career Opportunities

Graduates will be prepared to take on leading roles in the technological and scientific sectors. They may work as AI Engineers, Data Scientists, Machine Learning Specialists, or AI Researchers, finding opportunities in innovative companies, research laboratories, tech startups, and public institutions. The growing demand for artificial intelligence experts opens doors to careers in fields ranging from robotics to finance, as well as the videogame industry and industrial automation.

Study Plan Details

Nome Completo dell’Insegnamento

S.S.D.

CFU

 
 

Primo Semestre

 

 

 

Algoritmi e Complessità

INFO-01/A

9

 

Artificial and Swarm Intelligence

INFO-01/A

6

 

Machine Learning /oppure/  Crediti Liberi

====

6

 

Deep Learning: Core Models and Methods

INFO-01/A

6

 

Ulteriori Conoscenze Linguistiche

====

3

 
       

Secondo Semestre

 

 

 

Heuristics and Metaheuristics for Optimization and Learning

INFO-01/A

6

 

Deep Learning: Advanced Models and Methods

INFO-01/A

6

 

Numerical Methods for Scientific Computing

MATH-05/A

6

 

Sistemi Robotici /oppure/  Crediti Liberi

====

6

 

Insegnamento a Scelta dal Seguente Gruppo A1

 

 

        Semantic Web

INFO-01/A

6

 

        Advanced Computer Graphics

INFO-01/A

6

 

        Computer Vision

INFO-01/A

6

 

        Computer Security

INFO-01/A

6

 
       

Terzo Semestre

 

 

 

Knowledge Representation and Reasoning

INFO-01/A

6

 

Advanced Robotic and Autonomous Systems

INFO-01/A

6

 

Ottimizzazione

MATH-06/A

6

 

Stages e tirocini

====

6

 

Insegnamento a Scelta dal Seguente Gruppo A2

 

 

        Natural Language Processing

INFO-01/A

6

 

        Linguaggi Formali 

INFO-01/A

6

 

        Software Quality and Project Development

INFO-01/A

6

 

        Multimedia

INFO-01/A

6

 
       

Quarto Semestre

 

 

 

Artificial Intelligence for Language Processing

INFO-01/A

6

 

Generative Artificial Intelligence

INFO-01/A

6

 

Prova finale

====

18

 

 

 

 

 

TOTALE  CFU

 

120