The Department of Mathematics and Physics at Roma Tre University offers a unique opportunity for students who want in-depth knowledge of the field of Machine Learning and Data Analytics. The Master in Data Analytics (MDA) is a one-year program whose lectures are held entirely online, providing rigorous training in this field. Upon successful completion of the program, students are granted 60 ECTS credits. The MDA is sponsored by Netgroup, and has scientific partnerships with IAC-CNR (Institute for Applied Computing, National Research Council of Italy), INFN Roma Tre (National Institute of Nuclear Physics, Roma Tre section), and INFN CNAF, the national center for Research and Development on Information and Communication Technologies.
Sponsorship
Scientific partner

Master Organization

Enrollment for the 2021/2022 edition: now open; application closes on January 10, 2022.
Calendar: February 2022 ~ February 2023.
Duration: one academic year.
Credits: 60 CFU (ECTS).
Lessons: all lessons will be on-line, with both live streaming and playback.
Tuition fees: 2.000 euro.
Scholarships: four scholarships to fully waive tuition fees.
Contact: Master Secretary Micaela Mosca,
micaela.mosca@uniroma3.it
Dept. Mathematics & Physics, Roma Tre University

Finishing this Master program will prepare you for job titles such as: Data Scientist, Data Analyst, Business Intelligence Analyst, Data Engineer. MDA graduate students have access to a wide range of opportunities, from private companies and public administrations to research institutes. The program has agreements with several institutions to guarantee internships and job opportunities to the most outstanding students.

To receive further info or to stay update from MDA, please send an e-mail to master.data.analytics@uniroma3.it

A Modular Approach

Our MDA is organized along four different specializations:

  • 1) Machine Learning and Deep Learning– Introduction to Machine Learning; Python basics; Python for Data Science; MATLAB for Deep Learning; TensorFlow; Case studies of Deep Learning; Meta Learning; Languages for scalable data. 

  • 2) Social Data Analytics – Data analysis basics; Social data analytics; Text analytics & Natural Language Processing with Python; Corporate Analytics; Biotech data processing; Graph algorithms. 

  • 3) Digital PA – Digital public services; Cloud services; Cloud computing. 

  • 4) Data Security – Cryptography; Digital Currency; Privacy Enhancing Techniques in Data Analysis. 

Students will acquire in-depth understanding of the field through a rigorous and challenging program covering the fundamentals of Machine Learning and Deep Learning, analysis of Social Data and Business Intelligence, the digitalization of Public Services and Data Security. This will prepare students for successful professional careers. 

Graduates from any Course Degree in Mathematics or Physics from Roma Tre University will benefit of a 60% reduction in tuition fees. 

Students can also choose to enroll to single specializations or to single courses, and will receive a certificate of attendance after successful completion of their program. The Scientific Committee can advise the prospective students about personalized programs. 

Director: Prof. Stefano Maria Mari, full professor of Physics, Department of Mathematics and Physics, Roma Tre University. 

 

ML & DL

 

110 Hours/ 19 ECTS

Goal
Learn to analyse data using modern techniques of Machine Learning & Deep Learning to make better decisions; gain a solid foundation in statistics to better interpret your data. Then move beyond the basics by learning how to fine-tune and scale your models. Through the assignments of this specialisation, you will use the skills you have learned to produce mini-projects and apply your knowledge to real world problems.  

Program at glance
Prediction problems: classification and regression. Optimization of machine learning models. Software for ML & DL: Python, TensorFlow, MATLAB toolbox for Deep learning. Meta learning, and large-scale machine learning.  

 

Social Data Analytics

132 Hours / 21 ECTS 

Goal
We introduce concepts and techniques used for the analysis of social and business data, that is, typically unstructured data acquired by observing human behavior in different areas, or commercial data. 

Program at glance
Text mining analytics: language processing algorithms to analyze and understand languages by combining AI and advanced analytical techniques;
Sentiment analytics: sentiment analysis of unstructured data, primarily in the textual form; techniques to extract meaningful patterns from text.
Data Analysis for Business Intelligence: 
Reporting: Metrics & Key Performance Indicators, data visualization, dash-boarding; A/B testing: experimental designs, analysis and interpretation; Causal inference methods applied to business decisions making. 

 

Digital
PA

32 Hours / 5 ECTS 

Goal
Key issues for the digitalization of public services with a focus on: reimagine service journeys; enable rapid deployment and simplified integration with scalable IT architecture; empower central coordination unit with smart program management.

Program at glance
Digitalization of publicCloud services for PAHandling large Data base with sensitive data. Solution for recurring service transactions, such as identification or payment.

Data Security

48 Hours / 8 ECTS 

Goal
The goal of this specialization is to acquire key notions of cryptography and cybersecurity. 

Program at glance
Algorithmic complexity, probabilistic algorithms and adversary’s advantage, symmetric-key cryptography, public-key cryptography and other cryptographic primitives. Secure communication protocols: basic primitives, PKI, Multi-Party Computations. Security tokens: FIDO2 protocol. Key Management Systems: HSM, HSM as a service. Distributed Ledger Technology (blockchains): Bitcoin: consensus algorithm, forks, proof of work. Other currencies: Ethereum, zcashAlgorand. Smart contracts. Privacy: functional encryption, attribute-based encryption, full-homomorphic encryption, differential privacy, federated learning. Post Quantum Cryptography.