Master goal

The MDA aims at the professional development in the fields of Data Analytics, giving a completion to the knowledge acquired in a university degree. Moreover, MDA aims to keep you up to date on current trends on the application of ML & DL techniques to Data Analytics, as well as to help you develop new skills for the purpose of advancement in these fields. The MDA’s program encompasses the fundamental mathematical tools and specific software used to analyze data and extract insight from them; moreover, it tackles actual problems with the analysis of selected case studies.

The MDA is addressed to students with strong quantitative skills and a solid background in STEM, Statistics and Economics disciplines.

Master progress

The MDA has a one-year program, starting on February 2024 and finishing on February 2025. The MDA yields 60 ECTS through lectures, exercises, seminars, and final project. Lectures and exercises amount to 53 ECTS, corresponding to 322 hours of lectures. All lectures will be online, with the chance of attending both in streaming or in playback; lectures will be in Italian or English.

The MDA program has three specializations:

  1. Machine Learning (70 hours)
  2. CyberSecurity (50 hours)
  3. Science and Society (115 hours)

Moreover, the Master offers the opportunities of stages at our scientific partners IAC-CNR (Institute for Applied Computing, National Research Council of Italy) and INFN Roma Tre (National Institute of Nuclear Physics).

List of courses

The following courses may change a bit, soon you’ll see the upgrade
From this year we’ve upgraded not only some content but we’ve worked on a new and modern arrangement. Starting from 2024 due to the high number of courses the students are supposed to test their knowledge doing a work on similar courses all together and that’s why we show on next table the courses grouped by their affinity

Courses whose content has a certain affinity are listed in the same group, color-coded and identified with a number. For each group, only one overall exam is required; students must choose a professor and request an overall assigment.


Course Teacher & affiliation Hours/ECTS Program
F1 – Fundamentals
Python Basics Severino Bussino
Roma Tre University
15/3 Introduction to Python
Python Advanced I Paola Celio
Roma Tre University
10/2 Python advanced
Python Advanced II Paola Celio
Roma Tre University
10/2 Technical skills for data analysis
Database Paola Celio
Roma Tre University
10/2 Data Analysis
Basic Statistics Stefano Mari
Roma Tre University
15/3 Introduction to data analysis
Statistics of Extreme Event Stefano Mari
Roma Tre University
5/1 Introduction to data analysis
F2 – Fundamentals
Graph Algorithms Stefano Guarino
15/3 Introduction to scientific techniques
M1 – Machine Learning
Languages for scalable data Flavio Lombardi
15/3 Software for HPC Rust/Go/Python/Scala
Introduction to Machine Learning Vincenzo Bonifaci
Roma Tre University
10/2 Learning problems, regression, classification
Machine Learning Vincenzo Bonifaci
Roma Tre University
Explainable Machine Learning Gabriele Nocco
15/3 Explainable Machine Learning
M2 – Machine Learning
Sparse Methods for high-dimensional data Italia DeFeis 15/3 Sparse Methods for high-dimensional data
Introduction to Matlab Maurizio Ricci 6/1 Introduction to Matlab
Neural Networks with MATLAB Luciano Teresi
Roma Tre University
15/3 Matlab toolbox for Deep Learning
TensorFlow Louis Andrianaivo
Politecnico di Torino
15/3 Basic TensorFlow
MATLAB Workshop Alessio Conte 3/1 Mathworks
C1 – Cybersecurity      
Cryptography I Marco Pedicini
Roma Tre University
10/2 Encryption methods and applications
Cryptography II Elia Onofri
Roma Tre University
Cryptography: case study Marco Pedicini
Roma Tre University
C2 – Cybersecurity      
Cybersecurity, Cyber Intelligence and  Data Privacy Walter Arrighetti
Banca d’Italia
Digitalization for PA: Case Studies Walter Arrighetti
Banca d’Italia
15/3 Selected case studies of digitalization of public services
C3 – Cybersecurity      
Fintech and introduction to Crypto Currency Fabrizio Villani
Fintech Italia
15/3 Introduction to blockchain technology
S1 – Science & Society      
Social Data Analytics Ida Mele
15/3 Sentiment analysis of unstructured data
Text Analytics and Natural Language Processing Roberto Maieli
Roma Tre University
15/3 Language processing algorithms
S2 – Science & Society      
Cloud Computing Antonio Budano
15/3 Introduction to Cloud services Speaker: Dona Cristina Duma
Data Processing Lucia Morganti
5/1 Data Processing Speaker: Dona Cristina Duma
S3 – Science & Society      
Biotech Data Processing Matteo Rucco
Biocentis – Biotech Data Processing
15/3 Biotech Data Processing