Data Science and Management
The Master's Degree Programme in Data Science and Management is designed to develop the leaders of the future, equipping them with skills in artificial intelligence, data science and management through a comprehensive and balanced education.
With a practical and applied approach, the curriculum offers a competitive advantage for entering the world of work.
In an increasingly digitalised and data-driven environment, the programme is an advanced response to the needs of modern organisations, which require professionals capable of harnessing the power of data to drive innovation and meet the challenges of the digital revolution.
Degree Programme Class: LM-91
The Director
Blerina Sinaimeri
She is currently Associate Professor of Computer Science at LUISS Guido Carli University. Before joining LUISS, she was a tenured researcher (Chargée de recherche) at INRIA, the French National Institute for Research in Digital Science and Technology. She earned her PhD in Computer Science from Sapienza University of Rome in 2010.
Her research focuses on the algorithmic and computational aspects of graph theory, with applications to computational biology and the social sciences, particularly the study of the evolution of interacting systems. She has published in leading international journals, including Algorithmica, Theoretical Computer Science, Bioinformatics, and IEEE/ACM Transactions on Computational Biology and Bioinformatics.
She has taught at both undergraduate and graduate levels in Italy and France, including at LUISS, Université Lyon 1, the École Normale Supérieure de Lyon (ENS), and the Institut National des Sciences Appliquées de Lyon (INSA). She is also actively engaged in science outreach and public engagement initiatives.
The Master's Degree Programme in Data Science and Management is a two-year programme designed to provide students with advanced skills in the analysis of complex data and strategic decision-making.
First semester
Data-Driven Management
The course analyses how artificial intelligence and big data support managerial decisions in the main business areas - from logistics to production, from marketing to research and development, to finance and human resources management. The factors favouring their adoption and impact on decision-making processes are explored.
Data Science in Action
The course is designed to act as a missing link between model-based analysis and data-centric techniques. It uses numerous examples of real-life event logs to illustrate the concepts and algorithms presented in the other courses.
Data Visualization
The course provides an overview of the principles and tools of data visualisation. Accordingly, students learn how data analysis and visualisation work together to effectively communicate data-based results, motivate analysis and detect errors.
Statistical Foundations of Data Science
The course provides an overview of advanced statistical methods for data science, with emphasis on understanding the advantages and limitations of each approach, their interpretation, and their main applications in economics, business and management.
Computing Infrastructures for Data Science
The course introduces the fundamental concepts of computational infrastructures for data science. Students will become familiar with hardware and software architectures, distributed systems, cloud computing, and tools for the efficient management of large amounts of data, with a focus on scalability, reliability and performance aspects.
Second semester
Ethics for AI
The course focuses on the ethical issues of the most recent developments in artificial intelligence, with particular emphasis on algorithmic judgment.
Deep Learning
The course offers a comprehensive introduction to neural networks and deep learning. The main architectures (e.g. feedforward, convolutional and recurrent networks) and fundamental training techniques will be covered. Practical applications and experiential labs will complement the theoretical concepts.
Regulation for AI
The course builds a solid foundation on privacy and data protection law from a European and comparative perspective. It provides the tools to fairly and responsibly manage the processing of personal data in organisations.
Data Privacy and Security
The course provides essential knowledge on data privacy and cybersecurity, combining theoretical concepts with practical skills. Students will explore the fundamentals of modern cryptography, secure network communication, blockchain technologies and the main vulnerabilities of modern software.
Digital Ecosystems
The course reviews and analyses current theories of ecosystems in the fields of information systems, organisational studies, business strategy and innovation. Specific attention is dedicated to ecosystems that develop around the production, sharing, analysis and exchange of data.
Optimization Methods in Management Science
The course introduces students to the theory, algorithms and applications of optimisation. Methodologies covered include linear programming, optimisation over networks, integer programming and decision trees. Applications to various areas of business and management are covered.
First semester
Statistical Learning
The course covers advanced regression and classification methods for flexible modelling of complex data. The main topics covered include non-parametric techniques, Gaussian processes, kernel-based approaches and Reproducing Kernel Hilbert Spaces (RKHS), with a focus on possible applications to different areas of business and management.
Foundation Models
The course introduces students to the foundation models that power the most recent applications of artificial intelligence, in particular large language models (LLM). Architectures, pretraining techniques, scalability and adaptation to specific application contexts are analysed.
2 elective courses
Other ECTS
Certificate 1
Certificate 2
Internship or Project Work
Final Thesis
Total ECTS
Luiss offers numerous programs for students, which are accessible based on their current or future degree program.
- Dual degree programs for students enrolled in a master's degree program
- Erasmus and International Exchange Programs
- Free Mover Semester Abroad
- Summer Schools Abroad
Discover all the international programs and opportunities for experiences abroad offered by Luiss to enrich your academic and professional journey.
Admission procedures and requirements
Check out the useful information, procedures and deadlines for submitting an application to master's degree programmes at Luiss.
Tuition fees, scholarships and benefits
The annual single tuition fee for enrolment in the Master's Degree Programme in Data Science and Management is € 15,000.00, divided into 3 instalments, plus the regional student welfare tax.*
Luiss offers scholarships and partial or total exemptions from university tuition fees, also thanks to the support of public and private partners.
The University has also entered into agreements with Italian banks to offer flexible loans without collateral.
Check out all the opportunities related to Scholarships and Unsecured Loans.
*The amount of the regional student welfare tax will be decided by the Lazio Region in June/July 2026.
The degree program is subject to approval by the Ministry of University and may undergo modifications.
Career paths
The degree programme will develop new business leaders capable of effectively applying data-driven methodologies across multiple business domains.
By way of example, here are three potential career paths for graduates of this programme:
- Data Scientist: experts in solving complex problems through the use of advanced quantitative methodologies and computer science techniques, with the aim of extracting knowledge and strategic value from data.
- Data Intelligence Analyst: professionals capable of integrating data science methodologies into strategic and business processes.
- Data Manager: individuals responsible for managing, collecting processing of large data streams, with expertise in assessing their reliability, privacy and security.
Graduates and Employability
- The employment rate of Luiss graduates one year after graduation is 95%.
- The average time that passes between graduation and one’s first job is 1 month, with 70% of graduates already having a job offer before graduation.
- 12% of graduates work abroad.
- Luiss boasts an active network of over 500 employers: businesses, public and private institutions, and multinationals, which offer graduating students and recent graduates concrete job opportunities.
- In 2024, more than 3,200 placements were made between internships and jobs.
- More than 2,800 one-to-one career guidance meetings were provided to support students and recent graduates in their career paths.
- Over 5,000 students took part in networking and recruiting events, organised during 2024: more than 40 events, including 4 career fairs, with the involvement of over 300 employers and 90 Luiss alumni professionals.
