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 70 university credits (ECTS), 54 acquired through the frontal lectures, 15 acquired through the internship and 1 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 a Business or a Software Engineering program.

CORE PATH:

I term: 24 CFU
During the first term students will attend the following courses:

COURSES ECTS PILLAR
Supervised learning 6 Statistics techniques
Unsupervised 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

 

II term: 18 CFU

During the second term students will attend the following courses:

COURSES ECTS PILLAR
High Dimensional Time Series 3 Statistics
Machine learning 4 Computer Science
Architetctures, systems and algorithms for big data computing 3 Computer Science
Business cases 6 Business
Cloud & mobile 2 Networking

 

During the third term student can choose between a Business program and a Software Engineering program.

COMPUTER SCIENCE 

COURSES ECTS PILLAR
Text Mining and Document Analysis 3 Computer Science
Economic Complexity 3 Computer Science
Social Media Analysis and Recommendation Systems 3 Computer Science
Scientific Data Handling  and image processing 3  Computer Science

 

BUSINESS

COURSES ECTS PILLAR
Fundamental of Finance 3 Business
Strategic Marketing 3 Business
Marketing Analitics Lab 3 Business
Optional Course 3 Business

 

The internship will take place either at Telecom Italia S.p.A or Ericsson Telecomunicazioni S.p.A, leading companies in telecommunication sector. At the end of the Master Program, the students must produce a written final work (Master thesis) about the project work carried out during the internship, which will be discussed and assessed by the Faculty.

Lessons will start on January 11, 2016, and will end in December 2016.