Second cycle degree in

Data science

Class: LM-91 - Methods and techniques for the information society

Class LM-91 - Methods and techniques for the information society
Duration 2 years
Branch Padova
Language English
Tuition fees and scholarships
Programme coordinator MARCO FERRANTE
Access Open access with admission requirements

Next Calls for applications (international students) - A.Y. 2021/22:

  • 1st Call: 2 November 2020-2 February 2021 - APPLY NOW
  • 2nd Call: 2 March-2 June 2021(non-EU)/2 September (EU)

Big data is one of the key terms to our contemporary world: the existence of nearly limitless amounts of data that need to be collected, managed, analysed and processed by competent professionals, equipped with specific tools. If you wish to train as a data scientist you will receive a multidisciplinary learning path which combines technical skills (with methodologies borrowed from engineering, computer science, statistics and mathematics) with knowledge of different sectors in which data processing is needed. You will therefore be able to processes the data and translate it into information useful for cognitive and decision-making process. You will be able to work in companies that provide IT services, startups and high-tech companies, public administrations and research centers. The course is delivered entirely in English.

Curricula
BDMA; Data Science

  Find out more

Characteristics and objectives
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. The Graduated in this degree 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 informations.

Occupational opportunities
The Graduates will have jobs opportunity in Italy and abroad in
▪ internet companies, consulting companies;
▪ startups and high tech industries;
▪ public administrations;
▪ research centers.

Curricula
BDMA; Data Science

  Teaching list

1st Year HIGH DIMENSIONAL PROBABILITY FOR DATA SCIENCE [ MARCO FORMENTIN ] FINANCIAL MATHEMATICS FOR DATA SCIENCE [ MARTINO GRASSELLI ] STOCHASTIC METHODS [ MARCO FERRANTE ] OPTIMIZATION FOR DATA SCIENCE [ FRANCESCO RINALDI ] STATISTICAL LEARNING 1 (MOD. A) [ ALBERTO ROVERATO ] STATISTICAL LEARNING 2 (MOD. B) [ ALBERTO ROVERATO ] COGNITION AND COMPUTATION [ MARCO ZORZI ] MACHINE AND DEEP LEARNING (MOD. B) [ ALESSANDRO SPERDUTI ] MACHINE AND DEEP LEARNING (MOD. A) [ LAMBERTO BALLAN ] VISION AND COGNITIVE SERVICES [ LAMBERTO BALLAN ] STRUCTURAL BIOINFORMATICS [ DAMIANO PIOVESAN ] KNOWLEDGE AND DATA MINING [ LUCIANO SERAFINI ] FUNDAMENTALS OF INFORMATION SYSTEMS [ GIORGIO MARIA DI NUNZIO ] DEEP LEARNING [ ALESSANDRO SPERDUTI ] FINAL EXAMINATION MACHINE AND DEEP LEARNING (C.I.) [ LAMBERTO BALLAN ] STATISTICAL LEARNING (C.I.) [ ALBERTO ROVERATO ] 2nd Year BIOLOGICAL DATA BIOINFORMATICS OMICS IN HUMAN DISEASE MATHEMATICAL CELL BIOLOGY BUSINESS ECONOMIC AND FINANCIAL DATA STAGE STATISTICAL METHODS FOR HIGH DIMENSIONAL DATA COGNITIVE, BEHAVIORAL AND SOCIAL DATA HUMAN COMPUTER INTERACTION GAME THEORY PROCESS MINING HUMAN DATA ANALYTICS NETWORK SCIENCE BIG DATA COMPUTING