Course description

The program intends to build Data Scientists whose solid technical background is complemented by a multidisciplinary preparation on various fields in which big data emerge. Highly required by Industries, Consulting Companies and Public Institutions, Data Scientists design and implement the analysis of big data, and provide managers and stakeholders with a clear account of their results. Graduates will be able to master tools coming from Engineering, Computer Sciences, Statistics and Mathematics for collecting, managing and analyzing big data, and to translate their work into highly valuable information.

Course structure

First year

I semester

  • Fundamentals of Information Systems (12CFU)
  • Stochastic Methods (6 CFU).
  • Statistical Learning (part I) (6 CFU).
  • Cognitive, Behavioral and Social Data (6 CFU).

II semester

  • Algorithmic Methods and Machine Learning (12CFU)
  • Optimization for Data Science (6 CFU)
  • Statistical Learning (part II) (6 CFU)
  • Elective course (6 CFU)

Second year

I semester

  • Business Economic and Financial Data (6 CFU)
  • Biological data (6 CFU)
  • Elective course (6 CFU)
  • Elective course (6 CFU)
  • Elective course (6 CFU)

II semester

  • Stage and final exam (30 CFU)

List of elective courses

All courses are credited with 6 CFU

  • Game Theory. I semester
  • Introduction to Omic Disciplines. I semester
  • Mathematical models and numerical methods for big data, I semester
  • Computational Marketing. I semester
  • Law and Data. I semester
  • Computer and Network Security, I semester
  • Process Mining. I semester
  • Bioinformatics, I semester
  • Methods and Models for Combinatorial Optimization, I semester
  • Biology and Physiology, I semester
  • Human Computer Interaction, I semester
  • Network Science, I semester
  • Knowledge and Data Mining. II semester
  • Human Data Analytics. II semester
  • Big Data Computing, II semester
  • Structural Bioinformatics, II semester
  • Cognitive services, II semester
  • Bioinformatics & Computational Biology, II semester

Career opportunities

Graduates will have job opportunities in Italy and abroad in

  • internet companies, consulting companies
  • startups and high tech industries
  • public administrations
  • research centers.

Entry requirements

To be admitted to the course, basic knowledge of the following disciplines is required: Mathematics, Differential and integral calculus for functions of one or more real variables. Numerical sequences and infinite sums. Basic notions of linear Algebra. Basic notions of Probability, including random variables, expectation, Central Limit Theorem. Computer Science. Programming in high level language (e.g. Java, C, C++, Python). Computer architecture: CPU, memory, peripherals, networks, operating system. Algorithms and data structures.

This knowledge is verified by the achievement of:

  1. 30 ECTS in the following areas: MAT/01-09; SECS-S/01; SECS-P/06; INF/01; ING-INF/05 of which at least 12 in MAT/01-09; SECS-S/01; SECS-P/06; INF/01; and at least 8 in INF/01; ING-INF/05.
  2. Degree classification equivalent to at least 85/110.
  3. a careful analysis of the curriculum, in particular the contents of the courses in Mathematics and Computer Science.

Language requirements

B2 level of ENGLISH (reading and listening); no formal certificate is needed.

Program taught in:
  • English

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Last updated September 1, 2019
This course is Campus based
Start Date
Oct 2019
2 years
2,600 EUR
Fees for a.y. 2018/19. Fees can be significantly waived based on your “Equivalent Economic Status Index – ISEE”.
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