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University labeled Initiative of Excellence (IDEX)

MSc in DATA SCIENCES


Join the most strategic field of the digital economy and learn its fundamental methods and algorithms with the "Data Science" MSc program at Université Côte d'Azur!

Introduction

Data Science is an emergent field of activity, which will become increasingly vital to the digital economy in the coming years. This requirement is mainly due to our increasing capacities in data acquisition and processing. The "Data Science" MSc at Université Côte d'Azur prepares future specialists in mathematical techniques and computer tools necessary for the extraction of knowledge from masses of data.

Objectives

The "Data Sciences" program is a 2-year MSc at 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" MSc also leads to Ph.D. programs in the area of applied mathematics and computer sciences.

Program and content

The "Data Sciences" program is a 2-year MSc at 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" MSc also leads to Ph.D. programs in the area of applied mathematics and computer sciences.

First year:

S0: M10 - Refresher courses
S1: M11 - Statistical inference
M12 - Data mining and big data
M13 - Workshops and ethical aspects
S2: M14 - Theory of statistical learning
M15 - Practice of machine learning
M16 - Data visualization and distributed systems
M17 - Case studies
M18 - Options (track-dependent)
S3: M19 - Internships

Second year (track "Data Science for Research and Development", 5 modules to choose):
S1: 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
S2: M29 - Internship


Second year (track "Data Science for Marketing, Finance, Business and Development"):
S1: 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)

Tuition fees

Tuition fees: 4000€ per year - 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.

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.

Future carreers

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.