Master in Data Science and Management
Luiss Guido Carli
Key Information
Campus location
Rome, Italy
Languages
English
Study format
On-Campus
Duration
2 years
Pace
Full time
Tuition fees
EUR 13,300 / per year
Application deadline
31 May 2024
Earliest start date
Sep 2024
Introduction
Program Insight
Data Science and Management is at the forefront of the digital revolution, nurturing data scientists who excel in both technical-scientific (STEM) and business domains. With the enquiry-based educational model, students will take an active role in all the different pillars of their learning experience: project works with companies, hackathons, competitions, as well as interactions with top academics and industry leaders on hot topics such as artificial intelligence, machine learning and big data analytics, including their implications for businesses at both the national and international level.
International Opportunities
The Luiss Student Exchange Office promotes student exchanges within the Erasmus Program, as well as through bilateral exchange agreements with non-European universities.
Gallery
Admissions
Scholarships and Funding
Luiss University aims to inspire meaningful change in society by educating a new generation of successful students and graduates. To this end, the University invests in inclusion, social mobility and collective leadership by going beyond conventions, roles and goals to transform boundaries into horizons.
Our mission is to create a future fueled by an intertwining of knowledge, cultures, responsibility and passion. Social, cultural and gender diversity and sustainable development in the circular economy and in digitalization are the guiding principles in taking action for international students. Welcoming international students is one of our most important values, which is why Luiss University offers a variety of full and partial scholarships to talented students from all over the world each year.
Curriculum
Study Plan
I year - 2024-2025
- Data Science In Action, 6 Credits
- The course is designed to be the missing link between model-based analysis and data-centric techniques. It will make use of many examples of real-life event logs to illustrate and bring down to earth the concepts and algorithms presented in the other courses.
- Advanced Statistics, 6 Credits
- The course provides an overview of some advanced statistical methods for data science. The focus is on understanding the advantages and limitations of each approach, interpretation, and main applications in various disciplines, particularly in economics, business, and management.
- Python and R for Data Science (lab), 6 Credits
- The course aims at providing technical skills about coding aspects for data analysis. The Python programming language and the R environment are illustrated with a specific focus on those libraries, modules, and functions that allow the students to manage data effectively.
- Data-driven Innovation, 6 Credits
- The course provides a tool to understand the strong correlation that exists nowadays between the available data sources and the innovation path of an enterprise. Will be present case histories of real enterprises that have built innovation starting from data.
- Digital Ecosystems, 6 Credits
- The course reviews and analyzes current theories of ecosystems in the fields of Information Systems, Organization Studies, and Business Strategy and Innovation. In particular, ecosystems evolved around the production, sharing, analysis, and exchange of a variety of resources among which data figure prominently.
- Data Visualization, 6 Credits
- The course provides an overview of the principles and latest tools of data visualization. Students will learn how data analysis and visualization should work together to create a powerful way for communicating data-driven findings, motivating analyses, and detecting flaws.
- Internet and Network Economics, 6 Credits
- The course provides an understanding of the economics of the internet and the digital economy. It will provide students with concepts from economic theory to make sense of the significant transformations brought about by the emergence and diffusion of information and communication technologies.
- Data Privacy and Security, 6 Credits
- The course provides an in-depth understanding of data privacy and security in technology-enabled environments, and it focuses on technological solutions, methods, and practices for data protection in business organizations and peer-to-peer networks.
- Machine Learning, 6 Credits
- The course provides an in-depth understanding of the foundations, scope, and approaches of machine learning and it focuses on their application to problems in various disciplines, particularly in business and management.
II year - 2025-2026
- Big Data and Smart Data Analytics, 6 Credits
- The course will focus on fundamental algorithmic, statistical, and programming issues posed by big-data analytics, tackling major problems and techniques for extracting knowledge from massive amounts of data.
- Privacy in the Digital World, 6 Credits
- The goal of the course consists of building a solid background on privacy and data protection law from a European and a comparative perspective and equipping students with tools to manage personal data processing fairly and responsibly within organizations.
- International Operations and Global Supply Chain, 6 Credits
- The course seeks to supply knowledge and skills to apply operations and supply chain principles to international environments. The students will learn to design, plan, operate and control manufacturing, production, logistics, and operations systems within the supply chain framework.
- Ethics for Artificial Intelligence, 4 Credits
- The course focuses on the ethical issues involved in the latest developments of AI which are embedded in more and more facets of our lives, in particular on the algorithmic judgment at its core, which as of today is developing at an impressive speed.
- 2 Elective Courses, 12 Credits
Additional Credits
- Mandatory Language, 4 Credits
- Learning Innovation Activities, 2 Credits
- Internship or Project Work, 6 Credits
- GAP 1, 2 Credits
- GAP 2, 2 Credits
- Final Thesis, 16 Credits
Total: 120 Credits
Program Tuition Fee
Career Opportunities
Job opportunities
Data Science and Management will train the new business leaders who are able to effectively deploy data-driven methodologies for several business applications. To give an idea, the following three are possible job opportunities for this Master:
- Data Scientists, capable of tackling today’s complex problems through the deployment of suitable quantitative methodologies and computer science techniques, so to extract knowledge and business value from data.
- Data Intelligence Analysts, capable of integrating data science methodologies inside strategic and business processes.
- Data Managers, capable of coordinating the collection and processing of huge data flows, and to best practice for evaluating their reliability, privacy, and security.