Master of Science (MSc) DATA SCIENCEÂ
Master of Science (MSc) DATA SCIENCE
Objectives The «Data Sciences» Master is a 2-year MSc at the Université Côte d’Azur. It provides training in data science methods, emphasizing mathematical and compuer science perspectives. Students will receive a thorough grounding in theory, as well as learning the technical and practical skills of data science enabling them to apply advanced methods of data science to investigate real world questions. The core courses will provide students with comprehensive understanding of some of the most fundamental aspects of data, computational techniques and statistical analysis. Students will then choose courses from a range of optional modules ranging from Distributed Computing for Big Data and Statistical Computing, to Financial Statistics, Management and Marketing. The program will combine traditional lectures with computer lab sessions, in which students will work with data to complete hands-on exercises using programming tools, and analyze real data provided by professionals who are working in the industry. The «Data Science» Master also leads to Ph.D. programs in the area of applied mathematics and computer sciences.
Data Data Science Science is is an an emergent emergent field field of of activity, activity, which which will will become become inincreasingly vital to the digital economy in the coming years. This requicreasingly vital to the digital economy in the coming years. This requirement rement is is mainly mainly due due to to our our increasing increasing capacities capacities in in data data acquisition acquisition and and processing. The UCA «Data Science» Master of Science prepares future processing. The UCA «Data Science» Master of Science prepares future specialists specialists in in mathematical mathematical techniques techniques and and computer computer tools tools necessary necessary for for the extraction of knowledge from masses of data. the extraction of knowledge from masses of data.
Program First year: Semestre 0: M10 - Refresher courses Semestre 1: M11 - Statistical inference M12 - Data Mining and Big Data M13 - Workshops and ethical aspects
Semestre 2: M14 - Theory of Statistical learning M15 - Practice of Machine Learning M16 - Data Visualization and distributed systems M17 - Case studies M18 - Options(track-dependent) Semestre 3: M19 - Internships
Second year (track «Data Science for Research and Development», 5 modules to choose):
Second year (track «Data Science for Marketing, Finance, Business and Development»):
Semestre 1: M21 - Learning in high-dimensions M22 - Bayesian and advanced learning M23 - Data analysis M24 - Medical and networked data M25 - Random Fields and system performance M26 - Deep learning and web mining M27 - Information theory and smart cities M28 - Data streams and e-health
Semestre 1: M31 - Data Mining for Finance M32 - Big Data Applications for Financial Markets M33 - Marketing Modeling M34 - Management M35 - Mathematical Finance M36 - Case Studies M37 - Maths module (to choose in track A)
Semestre 2: M29 - Internship
Future careers Graduates will be competitive for positions both in private companies and public research institutes. They will be prepared to succeed in positions such as data scientists, data miners, or research assistants. Further research at the Ph.D.-level will prepare graduates for careers as research engineers or research. We also expect that our partners will offer several positions to our most competitive graduates.
Master of Science (MSc) Data Science
Admission Admission will be based on application files and, ultimately, on an interview. Applicants will be asked to write a proposal for a Data Science project that they will be able to develop during the first year if they are selected.
Tuition fees: 4000â‚Ź* *The tuition fee may vary according to your residence status, namely if you are a resident of an EU country or of a country outside the EU. In addition, financial aid (need-based or merit-based scholarships) will be available to students, and other sources of funding will also be available through each training course.
Partners
Contacts Prof. Frederic Mallet, I3S, Prof. BenoĂŽt Miramond, LEAT http://univ-cotedazur.fr/fr
msc-data-science@univ-cotedazur.fr