Course Structure

The program is designed around four pillars: Software Engineering, Statistical techniques, Telecommunication Engineering, and Business. All these subjects are needed to acquire the capacity to design, manage, and analyze Big Data.
The course implies activities for a total of 60 university credits (ECTS), 51 acquired through lectures and practical classes, and 9 acquired through a written final work (Master Thesis).
Class attendance will be compulsory. Classes will be held from Monday to Friday for 30 hours a week on average.
Lessons 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 and analyze Big Data. In the third term the student can choose 5 out of 7 elective courses.
Lessons will start on 14 January 2019, and will end in early June 2019.
Exams will take place in June-early July 2019.
After taking the exams, students shall produce a written final work (Master thesis), which corresponds to 9 ECTS. The Master thesis will be discussed in December 2019. 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.

 

CORE SUBJECTS:

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

Course

Academic discipline

Lectures Practice and seminars

ECTS

Supervised learning Economic Statistics

36

18

6

Unsupervised learning Statistics

36

18

6

Data management for big data analysis Informatics

18

9

3

Security & Privacy Telecommunications

18

9

3

II term: 18 ECTS

During the second term students will attend the following courses:

Course

Academic discipline

Lectures Practice and seminars

ECTS

High dimensional time series Economic Statistics

18

9

3

Topics in machine learning Informatics

24

12

4

Architectures and systems for big data Informatics

18

9

3

Cloud & mobile Telecommunications

12

6

2

Designing communication of results Organization and Human Resource Management

12

2

Decision making processes & models Organization and Human Resource Management

12

2

Strategic management of results Organization and Human Resource Management 12

2

ELECTIVE SUBJECTS:

III term: 15 ECTS

In the third term, the student should obtain 15 ECTS out of the following elective courses:

Course

Academic discipline

Lectures Practice and seminars

ECTS

Blockchain technology and applications Telecommunications

18

9

3

Economic complexity Theoretical Physics, Mathematical Models and Methods

18

9

3

Fundamentals of corporate finance Organization and Human Resource Management

18

3

Monitoring and processing for the Internet of People and Machines Telecommunications

18

9

3

Network virtualization and softwarization Telecommunications

18

9

3

Social media analysis Informatics

18

9

3

Text mining and document analysis Informatics

18

9

3