This MSc is designed for students having a strong bent for Computational, Statistical, and Mathematical Sciences and a genuine interest in working with data. Students will be taught cutting-edge techniques for extracting impactful information from large data sets and for effectively communicating them in order to influence the strategic decisions of the organizations where they will work.

The program is structured into two tracks sharing a modern quantitative core: Data Science and Business Analytics. They specifically pursue, to different extents, the following qualifying goals:

• Provide a strong foundation in theoretical and applied Statistics and in Machine Learning, that is essential for identifying effective models and methods for data analysis and prediction.
• Develop advanced skills in Computer Science that are crucial for building algorithms and programming tools suited for the actual implementation of statistical methods.
• Develop a profile that combines solid quantitative skills with in-depth knowledge of corporate dynamics to support management in making strategic decisions grounded in data analysis.
• Develop competencies, via educational activities inside and outside the classroom, that promote teamwork skills, ability to present and discuss the results of one’s work effectively, and that promote understanding of ethical and legislative limits related to the use of large-scale databases.

Upon the successful completion of this MSc program, students will have gained the necessary knowledge that makes them professional data scientists and business analysts who can readily contribute to companies, businesses, and institutions operating in a data-driven society. They will also have built the required background for pursuing Ph.D. programs in subject areas closely related to Data Science.

Program Structure

Main topics:

• Computer Science

• Statistics

• Machine Learning

• Business Analytics

• Marketing and Innovation

Data Science track

• Optimization

• Computer Science Algorithms

Business Analytics track

• Natural Language Processing

• Simulation and Modeling

Students will gain advanced and solid skills in the areas of Computer Science, Statistics, and Business Analytics, and will be introduced to tools and methodologies for collecting, processing, visualizing and analyzing large amounts of data (Big Data).

At the end of the first semester, students will choose one of the two tracks: Data Science and Business Analytics. The Data Science track focuses on statistical and computational methods with a strong emphasis on algorithms, mathematical optimization, modern stochastic modeling, and machine learning. The Business Analytics track focuses on Natural Language Processing, mathematical modeling and simulations, Finance, and Social Network Analysis.

2 electives

Data Science track

• Stochastic Processes

• Advanced Machine Learning

Business Analytics track

• Finance with Big Data

• Social Network Analysis

Students will also attend seminars for the development of behavioral abilities (e.g. teamwork; assertiveness and managing interpersonal relationships; public speaking; managing relationships in multicultural situations).

Internship (compulsory)
Foreign language (one EU language)
Thesis

Learning Objectives

Data Science and Business Analytics – taught in English – provides students with the most modern techniques of computational, mathematical and statistical analysis, to analyze large data sets (so-called Big Data), to interpret and communicate results in order to influence the strategic decisions of businesses and organizations where they will work.

Specifically, Data Science and Business Analytics’s qualifying goals are:

• To provide advanced preparation in the areas of the design and management of large databases, applied and theoretical statistics to identify correlations and causations in data to make predictions;

• To complete preparation in the area of Computer Science with advanced skills that allow the statistical skills acquired to be applied in order to influence the decision-making process in public organizations and companies;

• To develop a profile able to combine solid quantitative skills with in-depth knowledge of the corporate dynamics that enable relations with corporate management to influence strategic decisions based on data analysis;

• To develop behavioral skills via ad hoc seminars and via in/out of class activities related to courses, namely skills in communication, in interaction, in addressing complex issues; to develop competencies in understanding ethical and legislative limits related to the use of large-scale databases;

• To promote (besides English, the language of the program) proficiency in another EU language (Italian compulsory for non-native Italian speakers).

Career Opportunities

There currently is a huge demand for graduates in Data Science and Business Analytics on the job market. The possible career paths may be loosely related to the two tracks that characterize the program, namely: data scientist and business analyst.

Data scientists are recruited both by research centers within national and international institutions, tech companies and data-savvy companies operating in a wide range of industries that include healthcare, social media, finance, insurance, consulting, public utilities and pharma, just to mention a few.

Business analysts are required in any functional area within industrial and service companies in the public or private sector, especially consumer goods manufacturing firms, large retailers, consulting firms and public utilities companies.

The program also provides the necessary background for successfully undertaking a Ph.D. program in any of the following fields: Statistics, Applied Mathematics, Operations Research, Computer Science, Business and Management, Economics and Finance.

Moreover, graduates may take advantage of business, programming, and statistical skills acquired to start a company in the data-driven economy.

The MSc in Data Science and Business Analytics will be offered, starting from 2018-2019, therefore placement information is not yet available.