Incoming students

Computer Science

The Master Degree in Computer Science prepares the students to address technological future challenges. The course prepares the students with the competences to address autonomously complex issues and problems, by choosing the most appropriate solutions, as well as by creating and developing new enhanced solutions. The acquired competences enable graduates to cover responsibility and coordination positions in industrial contexts, to contribute to the technology transfer and to the research development. Further, these competences enable graduates to have a protagonist role in the development of the society of Information, and, thanks to the interdisciplinary applications of Computer Science, it will be possible to operate in business as well as social environments. The Master Degree offers advanced competences in the design and development of software, artificial intelligence, complex systems, data management, and machine learning. The acceptance requirements ensure a homogeneous base competences for all the candidates. These competences will be enriched and completed during a wide range of courses which will enable you to build your own path based on your own skills and expectations.

The courses are scheduled in two semesters: the first semester starts at the end of September and ends by mid-January, the second semester starts by the end of February and ends by mid-June. Exams and tests are held in January-February (Winter session) and since June to September (Summer session).

You can find below the list of the courses in English: courses taught in English or taught in English on demand if at least one incoming student will attend the course. For all the courses listed below, the exams will be taken in English or in Italian according to the incoming student preference. At the link for each Master degree, you can find the programs of the courses and the semester in which the courses are provided: you have to open the Syllabus of the course (Descrizione del corso), available both in Italian and in English.

Detailed programs at https://elearning.unimib.it/course/index.php?categoryid=3582

  • F1801Q107 - Complex Systems: Models and Simulation (on demand it will be taught in English) (6 CFU)
  • F1801Q122 - Information Theory and Cryptography (on demand it will be taught in English) (6 CFU)
  • F1801Q132 - Models and Computation (on demand it will be taught in English) (12 CFU) (*)
  • F1801Q151 - Advanced Machine Learning (it will be taught in English) (6 CFU)
  • F1801Q155 - Artificial Intelligence (on demand it will be taught in English) (6 CFU)
  • F1801Q157 - Cloud Computing (it will be taught in English) (6 CFU)
  • F1801Q149 - Computer and Robot Vision (on demand it will be taught in English) (6 CFU)
  • F1801Q153 - Data and Computational Biology (it will be taught in English) (6 CFU)
  • F1801Q161 - Causal networks (it will be taught in English) (6 CFU)
  • F1801Q158 - Evolution of Software Systems and Reverse Engineering (it will be taught in English) (6 CFU)
  • F1801Q141 - Logical Foundation of Computer Science (on demand it will be taught in English) (6 CFU)
  • F1801Q110 - Information Retrieval (it will be taught in English) (6 CFU)
  • F1801Q123 - Computer Security (on demand it will be taught in English) (6 CFU)
  • F1801Q117 - Parallel Computing (on demand it will be taught in English) (6 CFU)
  • F1801Q156 - Ubiquitous, Pervasive, & Context-aware Computing (it will be taught in English) (6 CFU)
  • F1801Q108 – Bioinformatics (on demand it will be taught in English) (6 CFU)
  • F1801Q162 – Large scale graph algorithms (it will be taught in English) (6 CFU)

(*) The course consists of two joint teachings, i.e. two different exams and one single final grade.

Detailed information about the Erasmus programs and the calls for applications are available at the University portal.

Data Science

The Master Degree in Data Science is part of the Class of Master Degrees in Information Society. The goal of the degree is to provide graduate students, who are coming from different scientific backgrounds, with advanced competences and skills required for the value-driven analysis of large amount of data (so called big data) using cutting-edge statistical techniques and computational models. The degree is targeted to graduate students who have a background in different scientific domains, ranging from Natural Sciences to Social Sciences and Economics. It is designed to have a solid basis in Statistics and Computer Science but also a strong multidisciplinary characterization in juridical, social and economic issues.

The courses are scheduled in two semesters: the first semester starts at the end of September and ends by mid-January, the second semester starts by the end of February and ends by mid-June. Exams and tests are held in January-February (Winter session) and since June to September (Summer session).

You can find below the list of the courses in English: courses taught in English or taught in English on demand if at least one incoming student will attend the course. For all the courses listed below, the exams will be taken in English or in Italian according to the incoming student preference. At the link for each Master degree, you can find the programs of the courses and the semester in which the courses are provided: you have to open the Syllabus of the course (Descrizione del corso), available both in Italian and in English.

Detailed programs at https://elearning.unimib.it/course/index.php?categoryid=4386

CURRENT

  • F9101Q011 - Data semantics (it will be taught in English)
  • F9101Q005 - Machine Learning and Decision Models (it will be taught in English) (*)
  • F9101Q021 - Social Media Analytics (it will be taught in English)
  • F9101Q017 - Streaming Data Management and Time Series Analysis  (it will be taught in English)
  • F9101Q021 - Social Media Analytics (it will be taught in English)
  • F9101Q013 - Technological Infrastructures for Data Science (it will be taught in English)
  • F9101Q015 - Text Mining and Search (it will be taught in English)

2022/2023

  • FDS01Q001 DATA MANAGEMENT AND VISUALIZATION (*)
  • FDS01Q002 MACHINE LEARNING AND DECISION MODELS (*)
  • FDS01Q003 DATA SCIENCE LAB
  • FDS01Q004 STATISTICAL MODELING
  • FDS01Q005 JURIDICAL AND SOCIAL ISSUES IN INFORMATION SOCIETY
  • FDS01Q006 FOUNDATIONS OF PROBABILITY AND STATISTICS
  • FDS01Q007 FINANCIAL MARKETS ANALYTICS
  • FDS01Q008 MARKETING ANALYTICS
  • FDS01Q009 FOUNDATIONS OF COMPUTER SCIENCE
  • FDS01Q010 DATA SEMANTICS
  • FDS01Q012 FOUNDATIONS OF DEEP LEARNING

2023/2024

  • FDS01Q001 DATA MANAGEMENT AND VISUALIZATION (*)
  • FDS01Q002 MACHINE LEARNING AND DECISION MODELS (*)
  • FDS01Q003 DATA SCIENCE LAB
  • FDS01Q004 STATISTICAL MODELING
  • FDS01Q005 JURIDICAL AND SOCIAL ISSUES IN INFORMATION SOCIETY
  • FDS01Q006 FOUNDATIONS OF PROBABILITY AND STATISTICS
  • FDS01Q007 FINANCIAL MARKETS ANALYTICS
  • FDS01Q008 MARKETING ANALYTICS
  • FDS01Q009 FOUNDATIONS OF COMPUTER SCIENCE
  • FDS01Q010 DATA SEMANTICS
  • FDS01Q012 FOUNDATIONS OF DEEP LEARNING
  • FDS01Q015 CYBERSECURITY FOR DATA SCIENCE
  • FDS01Q017 DIGITAL SIGNAL AND IMAGE MANAGEMENT
  • FDS01Q013 TEXT MINING AND SEARCH
  • FDS01Q022 HIGH DIMENSIONAL DATA ANALYSIS
  • FDS01Q023 STREAMING DATA MANAGEMENT AND TIME SERIES ANALYSIS
  • FDS01Q021 ECONOMICS FOR DATA SCIENCE
  • FDS01Q018 SOCIAL MEDIA ANALYTICS
  • FDS01Q019 SERVICE SCIENCE
  • FDS01Q020 BUSINESS INTELLIGENCE
  • FDS01Q024 DATA SCIENCE LAB IN ENVIRONMENT AND PHYSICS
  • FDS01Q025 DATA SCIENCE LAB IN BIOSCIENCES
  • FDS01Q026 DATA SCIENCE LAB IN MEDICINE
  • FDS01Q027 DATA SCIENCE LAB IN BUSINESS AND MARKETING
  • FDS01Q028 DATA SCIENCE LAB IN PUBLIC POLICIES AND SERVICES
  • FDS01Q016 TECHNOLOGICAL INFRASTRUCTURES FOR DATA SCIENCE
  • FDS01Q029 DATA SCIENCE LAB ON SMART CITIES
  • FDS01Q011 NATURAL LANGUAGE PROCESSING

(*) The course consists of two joint teachings, i.e. two different exams and one single final grade.

Detailed information about the Erasmus programs and the calls for applications are available at the University portal.

Theory and Technology of Communication

The Master Degree in Communication Theory and Technology belongs to the Class of Master's Degrees in Communication. The Master Degree aims to provide a solid cultural and methodological background in the computer science, psychological, visual and linguistic disciplines in the field of communication, with a strong multidisciplinary connotation, which will allow graduates to enter a job market in which professional figures with skills related to communication as cognitive and social process mediated or supported by technology are required. The main professional outlets are in the fields of digital communication and marketing, content creation and management, and the design of interactive digital systems.
The objectives of the course are to provide a high level of mastery of general scientific methods and contents and specific technical-professional knowledge that allow to play roles of high responsibility in the research, development and management of complex user-oriented communication systems and related technologies.
The teaching activity has an important project orientation: several courses have a laboratory approach, in which students of different training cooperate in working groups for the realization of projects with a strong multidisciplinary character.

The courses are scheduled in two semesters: the first semester starts at the end of September and ends by mid-January, the second semester starts by the end of February and ends by mid-June. Exams and tests are held in January-February (Winter session) and since June to September (Summer session).

You can find below the list of the courses in English: courses taught in English or taught in English on demand if at least one incoming student will attend the course. For all the courses listed below, the exams will be taken in English or in Italian according to the incoming student preference. At the link for each Master degree, you can find the programs of the courses and the semester in which the courses are provided: you have to open the Syllabus of the course (Descrizione del corso), available both in Italian and in English.

Detailed programs at https://elearning.unimib.it/course/index.php?categoryid=3588

  • F9201P211 - Multimedia Data Processing (it will be taught in English) (6 CFU)
  • F9201P213 - Applied Social Cognition to Public Policies (it will be taught in English) (8 CFU)
  • F9201P212 - Consumer psychology (it will be taught in English) (8 CFU)
  • F9201P208 - Data semantics (it will be taught in English) (6 CFU)
  • F9201P031 - Information Retrieval (it will be taught in English) (6 CFU)
  • F9201P210 - Ubiquitous, Pervasive, & Context-aware Computing (it will be taught in English) (6 CFU)

Detailed information about the Erasmus programs and the calls for applications are available at the University portal.

Artificial Intelligence

The courses are scheduled in two semesters: the first semester starts at the end of September and ends by mid-January, the second semester starts by the end of February and ends by mid-June. Exams and tests are held in January-February (Winter session) and since June to September (Summer session).

You can find below the list of the courses in English: courses taught in English or taught in English on demand if at least one incoming student will attend the course. For all the courses listed below, the exams will be taken in English or in Italian according to the incoming student preference. At the link for each Master degree, you can find the programs of the courses and the semester in which the courses are provided: you have to open the Syllabus of the course (Descrizione del corso), available both in Italian and in English.

Detailed programs at https://elearning.unimib.it/course/index.php?categoryid=9164

  • F9102Q012 – Embedded systems architectures and design (it will be taught in English) (6 CFU)
  • F9102Q008 – Advanced data management and decision support systems (it will be taught in English) (6 CFU)
  • F9102Q009 - Advanced artificial intelligence, machine learning and deep learning (it will be taught in English) (6 CFU)
  • F9102Q030 - Ambient intelligence (it will be taught in English) (12 CFU) (*)
  • F9102Q031 - Machine learning for modelling (it will be taught in English) (12 CFU) (*)
  • Intelligent consumer technologies (it will be taught in English)
  • Quantum information and algorithms (it will be taught in English)

(*) The course consists of two joint teachings, i.e. two different exams and one single final grade.

Detailed information about the Erasmus programs and the calls for applications are available at the University portal.

Accomodation

Looking for accomodation, flat/room? 

Contacts

Deputy for International Mobility at DISCo:
Prof. Fabio Stella
fabio.stella@unimib.it

Bachelor and Master Degrees in Computer Science Coordinator:
Prof. Simone Bianco
simone.bianco@unimib.it

Master Degree in Data Science Coordinator:
Prof.sa Elisabetta Fersini
elisabetta.fersini@unimib.it

Master Degree in Theory and Technology of Communication Coordinator:
Prof. Federico Cabitza
federico.cabitza@unimib.it