Course Structure

The program is designed around four pillars: advanced technologies in Software Engineering, Statistical techniques, Telecommunication Engineering, and Business. All these subjects are needed to acquire the capacity to design and manage Big Data:
The aim of the first period is the transmission of knowledge through traditional lectures, laboratory training and seminars. Class attendance will be compulsory. Classes will be held from Monday to Friday for 30 hours a week on average.
The course implies activities for a total of 60 university credits (ECTS), 54 acquired through the frontal lectures and 6 acquired through written final work (Master Thesis).
Frontal lectures are organized in three terms. In the first two terms, which are the core of the Program, the student will receive the basic knowledge needed to manage Big Data. In the third term the student can choose between elective courses.


I term: 18 CFU
During the first term students will attend the following courses:

Supervised Statistical Learning 6 Statistics techniques
Data Management for Big Data Analysis 3 Computer Science
Designing Communication of Results 2 Business
Decision Making Process & Models 2 Business
The Strategic Management of Big Data Results 2 Business
Security & Privacy 3 Networking

During the second term students will attend the following courses:II term: 18 CFU

High Dimensional Time Series 3 Statistics
Machine Learning 4 Computer Science
Architectures and Systems for Big Data 3 Computer Science
Cloud & Mobile 2 Networking
 Unsupervised Statistical Learning  6  Statistics techniques


III term: 18 CFU

In the third term, the student should obtain 18 ECTS credits out of the following courses:

Text Mining and Document Analysis 3 Computer Science
Economic Complexity 3 Computer Science
Social Media Analysis 3 Computer Science
Blockchain Technology and Applications 3 Networking
Business Cases 6 Business
Fundamentals of Corporate Finance 3 Business
Monitoring and Processing for the Internet of People and Machines 3 Networking
Network Virtualization and Softwarization 3 Networking
Strategic Marketing 3 Business

Lessons will start on 15 January 2017, and will end in early June 2017. Exams will take place in June-early July 2017.  After taking the exams the students shall produce a written final work (Master thesis), which corresponds to 6 ECTS credits. The Master theses will be discussed in December 2017. Its topic should be agreed with the coordinator of the program. The Master thesis could be also carried out during an internship in Italian or European companies and institutions. During the visiting as an intern, the student will have two tutors, one selected by the Master Coordinator and the second one indicated by the hosting institution.