The curriculum in Data Science and Applications is devoted to train experts in the management and analysis of data, particularly of Big Data. You will learn skills in statistics, modelling, data analytics, programming, high performance computing and management of databases for big data.
The curriculum is organized in common core courses (roughly I semester of I year), curriculum specific core courses (II semester of I year), and application specific courses (II year), depending on the application area/ study plan selected.
Common core courses:
- Advanced Programming and Algorithmic Design (12 CFU, I-II semester, I year)
- Foundations of High Performance Computing (9 CFU, I semester, I year)
- Introduction to Machine Learning (6 CFU, I semester, I year)
- Statistical Methods for Data Science (6 CFU, I semester, I year)
- Numerical Analysis (6 CFU, I semester, I year)
Curriculum specific core courses:
- Probabilistic Machine Learning (6 CFU, II semester, I year)
- Data Management for Big Data (9 CFU, II semester, I year)
- Unsupervised Learning (6 CFU, II semester, I year) for all specializations except Data Science for Social Sciences (see specializations below)
- Statistical Learning for Data Science (6 CFU, II Semester, I Year) only for Data Science for Social Sciences (see specializations below)
The study plans (application areas) available for the second year are the following:
- Data Management and Engineering
- Data Science for Health and Life Sciences
- Data Science for Social Sciences
- Geodata Science