MSc (LM) in Decision Science

The MSc (laurea magistrale) in Decision Science (LM-55), taught in English, aims to:
- Provide advanced skills in data analysis and decision-making.
- Prepare professionals to interpret modern economic phenomena and support strategic business decisions.
- Integrate knowledge of cognitive science, machine learning, artificial intelligence, and market analysis.
- Develop critical thinking, problem-solving, and effective communication skills.
The program aims to prepare qualified graduates with a strong multidisciplinary competences. A hybrid figure capable of analyzing phenomena through techniques typical of cognitive sciences, expert in quantitative methods, and capable of attributing a business meaning to numbers, algorithms and phenomena. In particular, the main professional profiles are:
- Business Data Scientist, who operates in support of market analysis, planning, strategic choices, with tasks related to data analysis to produce timely and relevant information for decision-making purposes. The graduate works closely with managers and clients to transform data into critical information and knowledge that can be used to inform the organization's strategic decisions.
- Cognitive Data Scientist, ranging from the analysis of business decisions to the analysis of clinical risk in the medical and healthcare sector; from the analysis of large datasets with multifactorial characteristics for the understanding of the mind-brain relationship to the analysis of cognitive and organizational processes underlying errors or organizational dysfunctions; from the design and implementation of basic and applied research projects (project management) to the management of interdisciplinary work teams.
Admission Requirements:
- Bachelor's degree in L-8 Information Engineering, L-9 Industrial Engineering, L-18 Business Administration and Management, L-24 Psychology, L-30 Physics, L-31 Computer Science, L-33 Economics, L-35 Maths, L-41 Statistics or equivalent qualification.
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For non-Italian qualifications: admission to the program is carried out through evaluation in terms of duration, acquired credits, and disciplinary content. The qualification must, in any case, allow enrollment in second-cycle courses in the country in which it was issued. The degree must be obtained within the deadline defined annually during educational planning.
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Graduates from other degrees can also access provided they demonstrate that they possess at least 30 credits in one or more of the following groups of scientific-disciplinary sectors:
- Physics and Maths
- Psychology
- Economics, Business Administration and Statistics
- Industrial and Information Engineering
- The possession of adequate skills to attend the course with profit will be verified by a specific Committee, formed by the Program Director and two professors of the program. Any curricular integrations, in terms of university credits, must be acquired before the verification of individual preparation. In any case, the program will offer crash courses related to the main disciplines based on the type of bachelor carried out.
- Knowledge of English language at B2 level at least.
Study plan
1st YEAR
|
Course |
SSD |
Credits |
|
1. Judgment and decision-making in applied contexts |
PSIC-01/A PSIC-03/B |
8 |
|
2. Dynamical models for social behavior |
PHYS-02/A |
8 |
|
3. Decision theory and human behavior |
ECON-07/A |
8 |
|
4. Cognitive neuroscience |
PSIC-01/B |
8 |
|
5. Data analysis for decision science |
PHYS-01/A |
8 |
|
6. Network science |
PHYS-06/A |
8 |
|
7. Digital marketing & analytics |
ECON-07/A |
6 |
|
8. Human-centered data analysis |
PHYS-06/A |
8 |
|
Laboratorio a scelta tra: - Storytelling & Public speaking - Exercise Leadership |
|
4 |
|
Laboratorio a scelta tra: - Laboratory of data analysis for decision science - Laboratory in measurement techniques for sustainable decision-making |
|
4 |
2nd YEAR
|
Course |
SSD |
Credits |
|
9. Computational psychometrics |
PSIC-01/C |
6 |
|
10. 1 elective among: |
||
|
Environmental data & indicators for decision makers |
AGRI-03/B |
6 |
|
Decision making in healthcare and law |
PSIC-01/A |
6 |
|
Artificial Intelligence applied to the music industry |
ECON-07/A |
6 |
|
Sensing technology for predictive modeling |
PHYS-01/A |
6 |
|
Psychology of social influence & persuasion |
PSIC-03/A |
6 |
|
Social media mining |
IINF-05/A |
6 |
|
Neuroscience of emotion and decision-making |
PSIC-01/B |
6 |
|
11. 1 elective among: |
||
|
Optimization models |
MATH-04/A |
6 |
|
Econometrics for Big Data (Panel data) |
ECON-05/A |
6 |
|
Game theory |
ECON-04/A |
6 |
|
Economic modeling of energy and climate systems |
ECON-02/A |
6 |
|
Cognitive sensors: from measurements to data and decisions |
PHYS-01/A |
6 |
|
Design Thinking |
ECON-07/A |
6 |
|
Life cycle assessment |
ECON-10/A |
6 |
|
|
|
|
|
12. Electives |
|
12 |
|
Internship |
|
10 |
|
Final dissertation |
|
10 |
For more information please refer to prof. Luca Petruzzellis