Human-Centered Artificial Intelligence

Human-Centered Artificial Intelligence
Scheda del corso
A.A. 2023/2024
Laurea magistrale
interateneo Università degli Studi di Milano-Bicocca, Università di Pavia
LM-55 - SCIENZE COGNITIVE
Human-centered artificial intelligence is a new paradigm that is now the focus of the research and development activities of both large companies and prestigious international research centers in the U.S. and Europe. The underlying idea is to shift the focus of Artificial Intelligence from "stand-alone" applications aimed at replacing humans in intelligent tasks to interactive applications in which human and machine intelligence work together to overcome the limitations of both.
The overall goal of this master's degree program is to train new professionals capable of accompanying the widespread diffusion of Artificial Intelligence in the professional world, enabling the reasonable and responsible integration of new technologies into the human context in which they are to be used. This integration aims to solve complex problems involving a constellation of non-technical variables: strategic goals, moral values, legal constraints, cognitive biases, and other psychological and social factors. From this perspective, the input of human agents becomes an integral part of an Artificial Intelligence system, and Artificial Intelligence itself becomes a set of sophisticated technologies to enhance the intelligence of human agents by expanding their cognitive capabilities. Hence, there is an essential need for strongly interdisciplinary skills to meaningfully and responsibly guide this process of integrating new technologies into the real-world contexts.
The aim is to train bridging figures between the hard-skills of experienced developers and the soft-skills needed to integrate AI applications into the human context in which they are deployed.
Graduates in Human-Centered AI will possess:
- significant education in the disciplines characterizing the interaction between human cognition and AI;
- a thorough understanding of the most advanced methods of data collection and analysis (machine learning);
- a thorough understanding of the theoretical, technical and cognitive aspects of human-computer interfaces;
- the ability to design models and interventions for the reorganization of interfaces between humans and AI systems;
- the ability to independently conduct research activities in the field of artificial intelligence;
- the ability to use fluently, in written and oral form, at least one language of the European Union besides Italian, with reference also to the terminology of the field;
- a thorough knowledge of a theoretical and operational nature on communication and decision-making processes based on the use of artificial intelligence systems;
- knowledge of the principles and the main methodologies of AI at a level adequate to interact fruitfully with computer scientists and connect them with domain experts;
- a thorough understanding of the non-technical aspects- e.g. ethical issues, legal constraints, cognitive aspects, philosophical foundations, neuroscientific foundations associated with the use of AI technologies to support, not replace, humans and their activities;
- familiarity with the main applications of AI in the work context (business, health care, legal) and with the tools that enable informed and transparent interactions between humans and machines.
Specific objectives will be formulated according to the curricula in which the course is organised. Since this is an interdisciplinary degree, which admits graduates from different backgrounds, these objectives will be achieved:
a) by including in the curriculum alternative courses that allow students to integrate their previously acquired knowledge according to the degree course of origin and the exams taken,
b) by proposing personalised study plans to guide students in their choices,
c) by proposing advanced foundations courses for the characterising subjects that are essential to the achievement of the training objectives, the purpose of which is to provide, in the initial part, a summary of the basic knowledge needed to acquire more advanced content,
d) by setting up a structured tutoring service to facilitate the use of these courses by students with different backgrounds.
Starting from a broad common core, the course will be divided into three curricula. The common core will consist of characterising subjects belonging to the following areas
1) philosophical and linguistic disciplines (with the addition of the areas M-FIL/03, IUS-20 and IUS-08), to acquire knowledge and competences of logical, epistemological and ethical-legal type
2) psychological disciplines, to acquire knowledge and competences on human-computer interaction and on the role of AI in decision-making processes
3) psychobiological and neuroscience disciplines, to acquire knowledge and skills relating to cognitive functions and their neural bases
4) mathematical, computer and engineering disciplines, to acquire knowledge and skills relating to machine learning models, algorithms and programming, knowledge representation and reasoning, natural language processing.
Laboratories aimed at acquiring further knowledge and skills in computing are also part of the common core.
The three curricula aim to provide a more specific preparation in relation to three main contexts:
A) the general context of integrating AI applications in an organisation and planning for fruitful collaboration between humans and machines, taking into account the psychological and social component of this interaction. This curriculum will provide:
- additional knowledge and skills in the field of AI, obtained through teaching in the fields of mathematics, computer science and engineering, as well as additional computer laboratories;
- knowledge and skills relating to the psycho-social and legal aspects of working in complex teams (made up of human beings with different skills and machines) and the impact of AI on the organisation of work, obtained through teaching in the field of psychology and related and complementary disciplines, with particular reference to sociology and anthropology.
B) The context of clinical and theoretical neuroscience. This curriculum will provide
- further knowledge and skills in the field of neural bases of brain processes for the development of AI-based, multiscale and bio-inspired neural models and for the handling of human-machine interface neural signals
- knowledge and skills relating to the application of AI algorithms in the field of clinical neuroscience, in order to promote the diagnostic and therapeutic/rehabilitation process in the direction of precision and personalised medicine.
C) The legal (domestic and European) as well as ethical context of AI applications in a public or private organisation. This curriculum will provide
- further knowledge and skills in the field of AI, adopting a multidisciplinary approach that enables the combination within the same teaching course (and laboratories) of the mathematical, computer and engineering disciplines relating to a specific field of application (judicial, public administration, tax, labour relations
etc.), with the respective and specific legal issues.
- knowledge and skills relating to the general ethical-legal aspects associated with AI applications, such as profiles relating to fundamental and human rights, data protection and data collection, civil and criminal liability, protection of intellectual property, communication, transparency.
All curricula guarantee, within the framework of the characterising disciplines, a minimum of 12 ECTS of computer science teaching in the first year, aimed at consolidating, or providing if necessary, fundamental knowledge and skills in this field. The laboratory activities also provide, for all students, the acquisition of at least further 9 ECTS in activities useful for acquiring computer skills.
The overall goal of this master's degree program is to train new professionals capable of accompanying the widespread diffusion of Artificial Intelligence in the professional world, enabling the reasonable and responsible integration of new technologies into the human context in which they are to be used. This integration aims to solve complex problems involving a constellation of non-technical variables: strategic goals, moral values, legal constraints, cognitive biases, and other psychological and social factors. From this perspective, the input of human agents becomes an integral part of an Artificial Intelligence system, and Artificial Intelligence itself becomes a set of sophisticated technologies to enhance the intelligence of human agents by expanding their cognitive capabilities. Hence, there is an essential need for strongly interdisciplinary skills to meaningfully and responsibly guide this process of integrating new technologies into the real-world contexts.
The aim is to train bridging figures between the hard-skills of experienced developers and the soft-skills needed to integrate AI applications into the human context in which they are deployed.
Graduates in Human-Centered AI will possess:
- significant education in the disciplines characterizing the interaction between human cognition and AI;
- a thorough understanding of the most advanced methods of data collection and analysis (machine learning);
- a thorough understanding of the theoretical, technical and cognitive aspects of human-computer interfaces;
- the ability to design models and interventions for the reorganization of interfaces between humans and AI systems;
- the ability to independently conduct research activities in the field of artificial intelligence;
- the ability to use fluently, in written and oral form, at least one language of the European Union besides Italian, with reference also to the terminology of the field;
- a thorough knowledge of a theoretical and operational nature on communication and decision-making processes based on the use of artificial intelligence systems;
- knowledge of the principles and the main methodologies of AI at a level adequate to interact fruitfully with computer scientists and connect them with domain experts;
- a thorough understanding of the non-technical aspects- e.g. ethical issues, legal constraints, cognitive aspects, philosophical foundations, neuroscientific foundations associated with the use of AI technologies to support, not replace, humans and their activities;
- familiarity with the main applications of AI in the work context (business, health care, legal) and with the tools that enable informed and transparent interactions between humans and machines.
Specific objectives will be formulated according to the curricula in which the course is organised. Since this is an interdisciplinary degree, which admits graduates from different backgrounds, these objectives will be achieved:
a) by including in the curriculum alternative courses that allow students to integrate their previously acquired knowledge according to the degree course of origin and the exams taken,
b) by proposing personalised study plans to guide students in their choices,
c) by proposing advanced foundations courses for the characterising subjects that are essential to the achievement of the training objectives, the purpose of which is to provide, in the initial part, a summary of the basic knowledge needed to acquire more advanced content,
d) by setting up a structured tutoring service to facilitate the use of these courses by students with different backgrounds.
Starting from a broad common core, the course will be divided into three curricula. The common core will consist of characterising subjects belonging to the following areas
1) philosophical and linguistic disciplines (with the addition of the areas M-FIL/03, IUS-20 and IUS-08), to acquire knowledge and competences of logical, epistemological and ethical-legal type
2) psychological disciplines, to acquire knowledge and competences on human-computer interaction and on the role of AI in decision-making processes
3) psychobiological and neuroscience disciplines, to acquire knowledge and skills relating to cognitive functions and their neural bases
4) mathematical, computer and engineering disciplines, to acquire knowledge and skills relating to machine learning models, algorithms and programming, knowledge representation and reasoning, natural language processing.
Laboratories aimed at acquiring further knowledge and skills in computing are also part of the common core.
The three curricula aim to provide a more specific preparation in relation to three main contexts:
A) the general context of integrating AI applications in an organisation and planning for fruitful collaboration between humans and machines, taking into account the psychological and social component of this interaction. This curriculum will provide:
- additional knowledge and skills in the field of AI, obtained through teaching in the fields of mathematics, computer science and engineering, as well as additional computer laboratories;
- knowledge and skills relating to the psycho-social and legal aspects of working in complex teams (made up of human beings with different skills and machines) and the impact of AI on the organisation of work, obtained through teaching in the field of psychology and related and complementary disciplines, with particular reference to sociology and anthropology.
B) The context of clinical and theoretical neuroscience. This curriculum will provide
- further knowledge and skills in the field of neural bases of brain processes for the development of AI-based, multiscale and bio-inspired neural models and for the handling of human-machine interface neural signals
- knowledge and skills relating to the application of AI algorithms in the field of clinical neuroscience, in order to promote the diagnostic and therapeutic/rehabilitation process in the direction of precision and personalised medicine.
C) The legal (domestic and European) as well as ethical context of AI applications in a public or private organisation. This curriculum will provide
- further knowledge and skills in the field of AI, adopting a multidisciplinary approach that enables the combination within the same teaching course (and laboratories) of the mathematical, computer and engineering disciplines relating to a specific field of application (judicial, public administration, tax, labour relations
etc.), with the respective and specific legal issues.
- knowledge and skills relating to the general ethical-legal aspects associated with AI applications, such as profiles relating to fundamental and human rights, data protection and data collection, civil and criminal liability, protection of intellectual property, communication, transparency.
All curricula guarantee, within the framework of the characterising disciplines, a minimum of 12 ECTS of computer science teaching in the first year, aimed at consolidating, or providing if necessary, fundamental knowledge and skills in this field. The laboratory activities also provide, for all students, the acquisition of at least further 9 ECTS in activities useful for acquiring computer skills.
Expert in Human-AI Cooperation
Function in a business context:
- Coordinating hybrid work teams (consisting of humans with different skills and machines), fostering interaction between IT experts, managers, domain experts, UX- designers and stakeholders.
- Organising the division of tasks and the ways of cooperation between humans and machines, taking into account psychological, ethical, sociological and cultural aspects.
- Translate stakeholders' needs in order to elaborate appropriate AI-based development projects within an organisation or company.
- Propose coaching and training sessions in which to illustrate to employees the benefits that human-machine hybrid teams can bring to the organisation.
- Coordinate collaboration with external consultants (economists, sociologists, analysts).
- Propose new performance indicators to assess the effectiveness of hybrid teams.
- Properly assess the ethical, psychological and social aspects of introducing artificial intelligence into the work environment and the general social context.
Skills associated with the function:
- Ability to make decisions on the basis of the logical-epistemological, cognitive and computing foundations of artificial intelligence;
- Ability to use data analysis and visualisation tools aimed at human-computer interaction;
- Ability to contribute to the development of applications of artificial intelligence in the fields of education, human sciences, art and culture;
- Ability to connect collaborators with different skills in order to effectively integrate artificial intelligence technologies in the work context.
Employment outlets:
The master's graduate will be able to find employment as an AI contact person in small and medium-sized companies, in enterprises and corporate groups, including those with a transnational dimension, in public administrations, independent authorities and national, EU and international agencies. He or she may also serve as a freelance consultant.
Expert in Neuro-AI
Function in a work setting:
- use virtual models of the brain to advance the diagnostic and therapeutic/rehabilitation pathway in the direction of precision and personalized medicine, in clinical neurology;
- interface the clinical setting with new AI-based ICT technologies;
- oversee the training activities of healthcare personnel by fostering the growth and dissemination of an "AI culture."
- adequately evaluate the ethical, psychological, and social aspects related to the introduction of artificial intelligence in the health and social context.
Competencies associated with the function:
- ability to make decisions based on the neuroscientific, cognitive and computer science foundations of AI;
- ability to analyze and visualize data, in the context of human-computer interaction;
- ability to coordinate a team composed of computer scientists and domain experts;
- ability to apply AI in the field of medicine.
Employment outlets:
Clinical facilities, both public and private, neuroscience centers, R&D departments developing digital and technological platforms for personalized and precision medicine, ICT departments in the biomedical field.
Expert in AI and Law
Function in a business context:
- apply AI techniques within the relevant legal framework of public agencies, private organizations, or international organizations;
- advise policy-making bodies and IT practitioners on the protection of rights in data collection and analysis operations and algorithmic decision-making processes;
- oversee the conscious use of AI by users or any civil and criminal liability profiles (for the user or the organization) arising from the use of innovative instrumentation;
- perform discrimination prevention and data protection oversight functions;
- oversee staff training activities by fostering the growth and dissemination of an "AI culture."
Skills associated with the function:
- ability to make decisions based on the legal, ethical, cognitive, and computer science foundations of AI;
- ability to work through AI methodologies employed in public and private organizations;
- ability to seize opportunities for the development of artificial intelligence, overseeing any civil or criminal liability profiles arising from its use;
- ability to coordinate a team composed of IT experts and domain experts;
- ability to interact with managers, IT experts and users of public and private organizations employing AI techniques in order to oversee the protection of the rights at stake.
Employment outlets:
Corporations and corporate groups, including those of transnational dimension; public administrations; independent authorities and national, EU and international agencies; self-employed.
Function in a business context:
- Coordinating hybrid work teams (consisting of humans with different skills and machines), fostering interaction between IT experts, managers, domain experts, UX- designers and stakeholders.
- Organising the division of tasks and the ways of cooperation between humans and machines, taking into account psychological, ethical, sociological and cultural aspects.
- Translate stakeholders' needs in order to elaborate appropriate AI-based development projects within an organisation or company.
- Propose coaching and training sessions in which to illustrate to employees the benefits that human-machine hybrid teams can bring to the organisation.
- Coordinate collaboration with external consultants (economists, sociologists, analysts).
- Propose new performance indicators to assess the effectiveness of hybrid teams.
- Properly assess the ethical, psychological and social aspects of introducing artificial intelligence into the work environment and the general social context.
Skills associated with the function:
- Ability to make decisions on the basis of the logical-epistemological, cognitive and computing foundations of artificial intelligence;
- Ability to use data analysis and visualisation tools aimed at human-computer interaction;
- Ability to contribute to the development of applications of artificial intelligence in the fields of education, human sciences, art and culture;
- Ability to connect collaborators with different skills in order to effectively integrate artificial intelligence technologies in the work context.
Employment outlets:
The master's graduate will be able to find employment as an AI contact person in small and medium-sized companies, in enterprises and corporate groups, including those with a transnational dimension, in public administrations, independent authorities and national, EU and international agencies. He or she may also serve as a freelance consultant.
Expert in Neuro-AI
Function in a work setting:
- use virtual models of the brain to advance the diagnostic and therapeutic/rehabilitation pathway in the direction of precision and personalized medicine, in clinical neurology;
- interface the clinical setting with new AI-based ICT technologies;
- oversee the training activities of healthcare personnel by fostering the growth and dissemination of an "AI culture."
- adequately evaluate the ethical, psychological, and social aspects related to the introduction of artificial intelligence in the health and social context.
Competencies associated with the function:
- ability to make decisions based on the neuroscientific, cognitive and computer science foundations of AI;
- ability to analyze and visualize data, in the context of human-computer interaction;
- ability to coordinate a team composed of computer scientists and domain experts;
- ability to apply AI in the field of medicine.
Employment outlets:
Clinical facilities, both public and private, neuroscience centers, R&D departments developing digital and technological platforms for personalized and precision medicine, ICT departments in the biomedical field.
Expert in AI and Law
Function in a business context:
- apply AI techniques within the relevant legal framework of public agencies, private organizations, or international organizations;
- advise policy-making bodies and IT practitioners on the protection of rights in data collection and analysis operations and algorithmic decision-making processes;
- oversee the conscious use of AI by users or any civil and criminal liability profiles (for the user or the organization) arising from the use of innovative instrumentation;
- perform discrimination prevention and data protection oversight functions;
- oversee staff training activities by fostering the growth and dissemination of an "AI culture."
Skills associated with the function:
- ability to make decisions based on the legal, ethical, cognitive, and computer science foundations of AI;
- ability to work through AI methodologies employed in public and private organizations;
- ability to seize opportunities for the development of artificial intelligence, overseeing any civil or criminal liability profiles arising from its use;
- ability to coordinate a team composed of IT experts and domain experts;
- ability to interact with managers, IT experts and users of public and private organizations employing AI techniques in order to oversee the protection of the rights at stake.
Employment outlets:
Corporations and corporate groups, including those of transnational dimension; public administrations; independent authorities and national, EU and international agencies; self-employed.
Attendance is recommended but not required.
Immatricolazione
Admission requirements
Admission to the Master in Human-Centered Artificial Intelligence requires a bachelor's degree or a three-year university degree, or a degree obtained abroad and recognized as suitable.
Basic knowledge in logical-epistemological, or mathematical-computer science or cognitive, philosophical or legal sciences is required to enter the Degree. Knowledge of the English language is also required.
Curricular requirements consist of the possession of at least 30 CFUs in the fields INF/01, ING-INF/05, MAT/01, 02, MAT/05, 07, 09, M-FIL/02, 03, 05, M-PSI/01, 02, BIO/09, IUS/01, IUS/08, 09, 20, of which:
- at least 12 in the fields INF/01, ING-INF/05, MAT/01, 02, MAT/05, 07, 09
- at least 12 in the fields M-FIL/02, 03, 05, M-PSI/01, 02, BIO/09, IUS/01, IUS/08, 09, 20.
Proficiency in English at a B2 level or higher per the Common European Framework of Reference for Languages (CEFR) is required for admission.
The B2-level requirement will be ascertained by the University Language Centre (SLAM) upon admission, by satisfaction of one of the following:
a) Having obtained a language certificate of B2 or higher level issued no more than three years before the date of admission application. You will find the list of language certificates recognized by the University at: https://www.unimi.it/en/node/297/. The certificate must be uploaded when submitting the online application;
b) Having obtained the open badge Bbetween English B2 from the University of Milan-Bicocca, or has passed the Placement test in English B2 from the University of Milan, or has obtained the English B2 certificate from the Language Center of the University of Pavia;
c) Holding a degree delivered entirely or predominantly in English;
d) English level achieved during a Bachelor's degree programme through SLAM courses and tests. The test must have been passed within the last four years. It will be assessed administratively, without the applicant having to attach any certificates.
All those who fail to submit a valid certificate or do not meet the required proficiency level will be instructed during the admission procedure to take the placement test administrated by the University Language Centre (SLAM) of the University of Milan according to the calendar published on the website: https://www.unimi.it/en/node/39267/
Applicants who do not take or pass the placement test will be required to obtain a language proficiency certificate recognized by the University and deliver it to the SLAM via the InformaStudenti service by the deadline fixed for the masters programme (https://www.unimi.it/en/node/39267/).
Applicants who do not meet the requirement by said deadline will not be admitted to the master's degree programme and may not sit any further tests.
Admission assessment
The Degree is open access. Admission is subject to verification of the possession of curricular requirements and evaluation of the candidate's personal preparation. For candidates with foreign degrees, verification of the requirements will be carried out by comparing the contents of the candidates' previous courses of studies.
Having verified the curricular requirements, the assessment of personal preparation will be done through individual interview on the knowledge required for admission. Specifically, basic knowledge in the area of algorithms and programming will be required for the computer science area; basic knowledge in the area of logic, probability and algebra will be required for the mathematics area.
In addition, basic knowledge in at least one of these three areas is required:
- philosophical: logic, epistemology and applied ethics;
- cognitive sciences: neuroscience, cognitive science and general psychology;
- legal: sources of law, fundamental rights and legal informatics.
The timing and procedures for submitting the application for the evaluation of qualifications, as well as the dates of the interviews will be published on the University website www.unimi.it on the page dedicated to the course of study.
Applicants with degrees from abroad will be attracted through widespread dissemination of open calls in all relevant fields through the academic networks of relevant faculty members. In their case, in order to appropriately assess the congruence of the educational background on the basis of the above curricular requirements, the admissions committee will decide on the appropriateness of admitting the candidate by evaluating the computer, mathematical, philosophical, psychological, biological and legal knowledge and skills acquired in his or her previous course of study, on the basis of an interview, including telematics.
Students must select a curriculum within the Master's degree programme upon submitting their application.
Admission to the Master in Human-Centered Artificial Intelligence requires a bachelor's degree or a three-year university degree, or a degree obtained abroad and recognized as suitable.
Basic knowledge in logical-epistemological, or mathematical-computer science or cognitive, philosophical or legal sciences is required to enter the Degree. Knowledge of the English language is also required.
Curricular requirements consist of the possession of at least 30 CFUs in the fields INF/01, ING-INF/05, MAT/01, 02, MAT/05, 07, 09, M-FIL/02, 03, 05, M-PSI/01, 02, BIO/09, IUS/01, IUS/08, 09, 20, of which:
- at least 12 in the fields INF/01, ING-INF/05, MAT/01, 02, MAT/05, 07, 09
- at least 12 in the fields M-FIL/02, 03, 05, M-PSI/01, 02, BIO/09, IUS/01, IUS/08, 09, 20.
Proficiency in English at a B2 level or higher per the Common European Framework of Reference for Languages (CEFR) is required for admission.
The B2-level requirement will be ascertained by the University Language Centre (SLAM) upon admission, by satisfaction of one of the following:
a) Having obtained a language certificate of B2 or higher level issued no more than three years before the date of admission application. You will find the list of language certificates recognized by the University at: https://www.unimi.it/en/node/297/. The certificate must be uploaded when submitting the online application;
b) Having obtained the open badge Bbetween English B2 from the University of Milan-Bicocca, or has passed the Placement test in English B2 from the University of Milan, or has obtained the English B2 certificate from the Language Center of the University of Pavia;
c) Holding a degree delivered entirely or predominantly in English;
d) English level achieved during a Bachelor's degree programme through SLAM courses and tests. The test must have been passed within the last four years. It will be assessed administratively, without the applicant having to attach any certificates.
All those who fail to submit a valid certificate or do not meet the required proficiency level will be instructed during the admission procedure to take the placement test administrated by the University Language Centre (SLAM) of the University of Milan according to the calendar published on the website: https://www.unimi.it/en/node/39267/
Applicants who do not take or pass the placement test will be required to obtain a language proficiency certificate recognized by the University and deliver it to the SLAM via the InformaStudenti service by the deadline fixed for the masters programme (https://www.unimi.it/en/node/39267/).
Applicants who do not meet the requirement by said deadline will not be admitted to the master's degree programme and may not sit any further tests.
Admission assessment
The Degree is open access. Admission is subject to verification of the possession of curricular requirements and evaluation of the candidate's personal preparation. For candidates with foreign degrees, verification of the requirements will be carried out by comparing the contents of the candidates' previous courses of studies.
Having verified the curricular requirements, the assessment of personal preparation will be done through individual interview on the knowledge required for admission. Specifically, basic knowledge in the area of algorithms and programming will be required for the computer science area; basic knowledge in the area of logic, probability and algebra will be required for the mathematics area.
In addition, basic knowledge in at least one of these three areas is required:
- philosophical: logic, epistemology and applied ethics;
- cognitive sciences: neuroscience, cognitive science and general psychology;
- legal: sources of law, fundamental rights and legal informatics.
The timing and procedures for submitting the application for the evaluation of qualifications, as well as the dates of the interviews will be published on the University website www.unimi.it on the page dedicated to the course of study.
Applicants with degrees from abroad will be attracted through widespread dissemination of open calls in all relevant fields through the academic networks of relevant faculty members. In their case, in order to appropriately assess the congruence of the educational background on the basis of the above curricular requirements, the admissions committee will decide on the appropriateness of admitting the candidate by evaluating the computer, mathematical, philosophical, psychological, biological and legal knowledge and skills acquired in his or her previous course of study, on the basis of an interview, including telematics.
Students must select a curriculum within the Master's degree programme upon submitting their application.
Ammissione
Domanda di ammissione: dal 27/03/2023 al 31/10/2023
Domanda di immatricolazione: dal 03/04/2023 al 15/01/2024
Allegati e documenti
Servizi online
Per approfondire:
Manifesto ed elenco insegnamenti
Obbligatorio
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Ai and human decision-making | 12 | 96 | Inglese | Secondo semestre | M-PSI/01 |
Ai, ethics and law | 6 | 48 | Inglese | Primo semestre | IUS/20 M-FIL/03 |
Brain and cognition | 6 | 48 | Inglese | Primo semestre | M-PSI/02 |
Machine learning | 6 | 48 | Inglese | Primo semestre | INF/01 |
Mathematics for ai | 6 | 48 | Inglese | Secondo semestre | MAT/07 |
Workshop: programming lab | 3 | 36 | Inglese | Primo semestre |
Attività a scelta e regole di composizione del piano didattico
A1 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Knowledge representation and reasoning | 6 | 48 | Inglese | Primo semestre | INF/01 |
Natural language processing | 6 | 48 | Inglese | Primo semestre | INF/01 |
Programming | 6 | 48 | Inglese | Primo semestre | INF/01 |
A2 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Logics for ai | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
Philosophy of cognitive neuroscience | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
The epistemology of big data | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
A3 - 6 ECTS in
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Principles of social psichology for ai design | 6 | 48 | Inglese | Secondo semestre | M-PSI/05 |
- 3 ECTS in a second EU foreign Language for Italian students ONLY
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Accertamento linguistico: lingua francese (3 CFU) | 3 | 0 | Italiano | Periodo non definito | |
Accertamento linguistico: lingua spagnola (3 CFU) | 3 | 0 | Italiano | Periodo non definito | |
Accertamento linguistico: lingua tedesca (3 CFU) | 3 | 0 | Italiano | Periodo non definito |
- 3 ECTS in Italian Language for foreign students ONLY
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Additional language skills: italian (3 ECTS) | 3 | 0 | Italiano | Periodo non definito |
sarà attivato dall'A.A. 2024/2025
Attività a scelta e regole di composizione del piano didattico
A5 - 1 workshop to choose between:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Workshop: software tools for machine learning | 3 | 36 | Inglese | ||
Workshop: software tools for statistics | 3 | 36 | Inglese |
A6 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Ai in education | 6 | 48 | Inglese | M-PED/03 | |
Media theory and ai | 6 | 48 | Inglese | L-ART/06 M-FIL/04 | |
Technological transfer | 6 | 48 | Inglese | SECS-P/08 |
A7 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Affective computing | 6 | 48 | Inglese | INF/01 | |
Human-computer interaction | 6 | 48 | Inglese | Primo semestre | INF/01 |
Knowledge representation and reasoning | 6 | 48 | Inglese | Primo semestre | INF/01 |
Natural language processing | 6 | 48 | Inglese | Primo semestre | INF/01 |
Text and argument mining | 6 | 48 | Inglese | INF/01 |
A8 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Anthropology of ai | 6 | 48 | Inglese | M-DEA/01 | |
Smart contracts and intellectual property law | 6 | 48 | Inglese | INF/01 IUS/01 | |
Sociology of ai | 6 | 48 | Inglese | SPS/08 |
A9 - 1 workshop to choose between:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Workshop: data visualization | 3 | 36 | Inglese | ||
Workshop: team management | 3 | 36 | Inglese |
A9_1 - 3 ECTS to be earned through a stage or a workshop among the ones offered by the course
Obbligatorio
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Final exam | 21 | 0 | Inglese | Periodo non definito |
Attività a scelta e regole di composizione del piano didattico
- 12 ECTS to be earned through any of the elective courses among those offered by the University of Milan, or University of Milano-Bicocca or University of Pavia.
There are no propaedeutic courses
Obbligatorio
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Ai and human decision-making | 12 | 96 | Inglese | Secondo semestre | M-PSI/01 |
Ai and media law | 6 | 48 | Inglese | Secondo semestre | IUS/08 |
Ai, ethics and law | 6 | 48 | Inglese | Primo semestre | IUS/20 M-FIL/03 |
Brain and cognition | 6 | 48 | Inglese | Primo semestre | M-PSI/02 |
Data protection, law and ai | 6 | 48 | Inglese | Secondo semestre | IUS/20 |
Machine learning | 6 | 48 | Inglese | Primo semestre | INF/01 |
Workshop: programming lab | 3 | 36 | Inglese | Primo semestre |
Attività a scelta e regole di composizione del piano didattico
B1 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Knowledge representation and reasoning | 6 | 48 | Inglese | Primo semestre | INF/01 |
Natural language processing | 6 | 48 | Inglese | Primo semestre | INF/01 |
Programming | 6 | 48 | Inglese | Primo semestre | INF/01 |
B2 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Logics for ai | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
Philosophy of cognitive neuroscience | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
The epistemology of big data | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
- 3 ECTS in a second EU foreign Language for Italian students ONLY
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Accertamento linguistico: lingua francese (3 CFU) | 3 | 0 | Italiano | Periodo non definito | |
Accertamento linguistico: lingua spagnola (3 CFU) | 3 | 0 | Italiano | Periodo non definito | |
Accertamento linguistico: lingua tedesca (3 CFU) | 3 | 0 | Italiano | Periodo non definito |
- 3 ECTS in Italian Language for foreign students ONLY
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Additional language skills: italian (3 ECTS) | 3 | 0 | Italiano | Periodo non definito |
sarà attivato dall'A.A. 2024/2025
Attività a scelta e regole di composizione del piano didattico
B4 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Corporate governance and ai | 6 | 48 | Inglese | IUS/04 | |
Responsibility and ai | 6 | 48 | Inglese | IUS/02 IUS/14 | |
Sources of law and fundamental rights in ai | 6 | 48 | Inglese | IUS/08 |
B5 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Data analysis and tax compliance | 6 | 48 | Inglese | IUS/12 SECS-S/01 | |
Digital surveillance, employee monitoring and selection by ai | 6 | 48 | Inglese | IUS/07 | |
Justice by algorithm | 6 | 36 | Inglese | INF/01 IUS/16 |
B6 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Ai and public administration | 6 | 36 | Inglese | INF/01 IUS/10 | |
Banking and insurance law | 6 | 48 | Inglese | IUS/04 MAT/06 | |
Multilevel protection of rights in ai | 6 | 48 | Inglese | IUS/13 IUS/14 | |
Smart contracts and intellectual property law | 6 | 48 | Inglese | INF/01 IUS/01 |
B7 - 1 workshop to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Workshop: employee monitoring and recruitment | 3 | 36 | Inglese | ||
Workshop: forensics | 3 | 36 | Inglese | ||
Workshop: tax data analysis and tax risk | 3 | 36 | Inglese |
B8 - 1 workshop to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Workshop: software tools for machine learning | 3 | 36 | Inglese | ||
Workshop: software tools for statistics | 3 | 36 | Inglese |
B9 - 3 ECTS to be earned through a stage or a workshop among the ones offered by the course
Obbligatorio
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Final exam | 21 | 0 | Inglese | Periodo non definito |
Attività a scelta e regole di composizione del piano didattico
- 12 ECTS to be earned through any of the elective courses among those offered by the University of Milan, or University of Milano-Bicocca or University of Pavia.
There are no propaedeutic courses
Obbligatorio
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Ai and human decision-making | 12 | 96 | Inglese | Secondo semestre | M-PSI/01 |
Ai, ethics and law | 6 | 48 | Inglese | Primo semestre | IUS/20 M-FIL/03 |
Brain and cognition | 6 | 48 | Inglese | Primo semestre | M-PSI/02 |
Brain modelling for biomedicine and ict | 6 | 48 | Inglese | Secondo semestre | BIO/09 |
Machine learning | 6 | 48 | Inglese | Primo semestre | INF/01 |
Neurophysiology and biophysics for ai | 6 | 48 | Inglese | Secondo semestre | BIO/09 |
Workshop: programming lab | 3 | 36 | Inglese | Primo semestre |
Attività a scelta e regole di composizione del piano didattico
C1 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Knowledge representation and reasoning | 6 | 48 | Inglese | Primo semestre | INF/01 |
Natural language processing | 6 | 48 | Inglese | Primo semestre | INF/01 |
Programming | 6 | 48 | Inglese | Primo semestre | INF/01 |
C2 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Logics for ai | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
Philosophy of cognitive neuroscience | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
The epistemology of big data | 6 | 48 | Inglese | Secondo semestre | M-FIL/02 |
- 3 ECTS in a second EU foreign Language for Italian students ONLY
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Accertamento linguistico: lingua francese (3 CFU) | 3 | 0 | Italiano | Periodo non definito | |
Accertamento linguistico: lingua spagnola (3 CFU) | 3 | 0 | Italiano | Periodo non definito | |
Accertamento linguistico: lingua tedesca (3 CFU) | 3 | 0 | Italiano | Periodo non definito |
- 3 ECTS in Italian Language for foreign students ONLY
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Additional language skills: italian (3 ECTS) | 3 | 0 | Italiano | Periodo non definito |
sarà attivato dall'A.A. 2024/2025
Obbligatorio
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Ai applied to neuroimaging | 6 | 48 | Inglese | FIS/07 MED/37 | |
Ai applied to neurological sciences and brain-computer interfaces | 6 | 48 | Inglese | M-PSI/02 MED/26 |
Attività a scelta e regole di composizione del piano didattico
C4 - 1 exam to choose among:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Human-computer interaction | 6 | 48 | Inglese | Primo semestre | INF/01 |
Machine learning for collaborative intelligent systems | 6 | 48 | Inglese | ING-INF/05 | |
Neuromorphic computing for ai solutions and neuro-robotics | 6 | 48 | Inglese | ING-INF/05 ING-INF/06 |
C5 - 1 workshop to choose between:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Workshop: software tools for machine learning | 3 | 36 | Inglese | ||
Workshop: software tools for statistics | 3 | 36 | Inglese |
C6 - 1 workshop to choose between:
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Workshop: neuromorphic and neurorobotics | 3 | 36 | Inglese | ||
Workshop: neuroplasticity and non-invasive brain stimulation techniques | 3 | 36 | Inglese |
C7 - 3 ECTS to be earned through a stage or a workshop among the ones offered by the course
Obbligatorio
Attività formative | Crediti | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Final exam | 21 | 0 | Inglese | Periodo non definito |
Attività a scelta e regole di composizione del piano didattico
- 12 ECTS to be earned through any of the elective courses among those offered by the University of Milan, or University of Milano-Bicocca or University of Pavia.
There are no propaedeutic courses
Altre informazioni
Tutor per l'orientamento
Tutor per la mobilità internazionale e l'Erasmus
Penaloza Nyssen Rafael
Tutor per i piani di studio
Tutor per stage e tirocini
Caverzasi Eduardo
Tutor per laboratori e altre attività
Tutor per tesi di laurea
Tutor per ammissioni lauree magistrali
Strutture di riferimento
Contatti
- Student registrar
Via S. Sofia 9/1 - 20122 Milano
https://www.unimi.it/it/studiare/servizi-gli-studenti/segreterie-informastudenti - Teaching office
Via Festa del Perdono, 3 - 20122 Milano (MI)
+39Phone 02 503 12724-12435
Le tasse universitarie per gli studenti iscritti ai corsi di laurea, di laurea magistrale e a ciclo unico sono suddivise in due rate con modalità di calcolo e tempi di pagamento diversi:
- l'importo della prima rata è uguale per tutti
- l'importo della seconda rata varia in base al valore ISEE Università, al Corso di laurea di iscrizione e alla posizione (in corso/fuori corso da un anno oppure fuori corso da più di un anno).
- per i corsi on line è prevista una rata suppletiva.
Sono previste:
- agevolazioni per gli studenti con elevati requisiti di merito
- importi diversificati in base al Paese di provenienza per gli studenti internazionali con reddito e patrimonio all'estero
- agevolazioni per gli studenti internazionali con status di rifugiato
Altre agevolazioni
L’Ateneo fornisce agevolazioni economiche a favore dei propri studenti con requisiti particolari (merito, condizioni economiche o personali, studenti internazionali)
Maggiori informazioni
Orientamento:
Info su ammissioni e immatricolazioni
- Contatta le segreterie
- Sportello online InformaStudenti (richiede la registrazione)
- Studenti internazionali: welcome desk
- Servizi per studenti con disabilità
- Servizi per studenti con DSA