MSc Data Science and Artificial Intelligence

 

Context

 

Data Science & Artificial Intelligence

Data Science and artificial intelligence (AI) are the emergent fields of activity with the most important needs within the digital economy in the coming years. This need is mainly due to the increasing capacities in data acquisition and processing. The UCA master «Data Science» trains specialists in mathematical techniques and computer tools necessary for the extraction of knowledge from masses of data. Join the most strategic field of the digital economy and learn its fundamental methods and algorith ms with the master "Data Science" of UCA! 

 What we offer

The master "Data Science & AI" is a 2 year MSc run by Université Côte d’Azur. It provides training in data science and AI methods, emphasizing mathematical and computer science perspectives. Students will receive a thorough grounding in theory as well as learn technical and practical skills of data science, enabling them to apply advanced methods of data science and AI to investigate real world questions. The core courses will provide students with comprehensive coverage of some 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 programme will combine traditional lectures with computer lab sessions, in which students will work with data to complete hands on exercises using programming tools or on real data brought by professionals working in the industry. The MSc "Data Science & Artificial Intelligence" also leads to Ph. D. programs in the area of applied mathematics, computer sciences and AI. 

 

Objectives

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Become a real Data Scientist!

Our interdisciplinary approach, combined with innovative learning methods, allows students to obtain positions in private companies and public research institutes. They could pretend to positions such as data scientist, data miner, research assistant and, after a Ph.D., research engineer and researcher in Data Science of Artificial Intelligence. 

Program

Books

 We detail hereafter the courses of the two years of the MSc. Notice that it is possible to apply directly to the 2nd year for students who already completed a 1st or 2nd year of a Master program.

 

1st year

Refresher courses (at least 2)

Basic Probability

Basic Algebra for Data Analysis

Basic Algorithmic

Basic tools for System Management

Semester 1


Statistical inference: theory and practice I & II
Processing large datasets with R
Data visualization
A general introduction to Data Mining
Technologies for Big Data with Python
Distributed Big Data Systems
Security and ethical aspects of data
Workshops

Semester 2


Theory of Statistical learning I & II
Machine Learning: from theory to practice I & II
Case studies
Model selection and resampling methods
Optimization for Data Science
Web of Data
Parallel Programming
Digital Marketing
Internship 4 months

 

2nd year 

Semester 3


Statistical Learning in High Dimensions
Bayesian Learning
Distributed Optimization and Games
Advanced Learning: functional, mixed and text data
Statistical Analysis of Graphs
Medical Image Processing
Deep Learning
Introduction to Information Theory
Optimization under constraints
Tensor Decompositions: models, algorithms and applications
Computer Vision
Workshops

Semester 4

Internship 6 months

Applications

What is a UCA Idex program?

Université Côte d'Azur (UCA) was established in 2016 from the merger between Université Nice Sophia Antipolis (UNS) and regional private partners. Within this new entity, some programs have been awarded the "Idex" label, for "Initiative d'Excellence", a very selective program that has three main requirements: international visibility, strong cooperation between schools, universities and organizations, and extensive regional integration. The Data Science MSc is one such program.

The program is fully taught in English. It benefits from innovative teaching methods (reinforced interactions, rich course content, integrated projects, etc.) and the program has been developed from a skills-based approach with potential employers. Part of the curriculum is available online for increased flexibility in the case of short absences, work commitments, or if you live on the other side of the planet (however your presence will be mandatory for certain parts of the program). Students will benefit from the scientific expertise of the laboratories of the Côte d'Azur, and the environmental management approach of Skema and Edhec Business schools.

 

Tuition fees

The registration fee is 4000 euros per year. The tuition fees may vary according to your residence status, namely if you are a resident of an EU county or of a country outside the EU.

 

Requirements

  • Students who start the Data Science program in the first year must be fluent in English and have an established background in Mathematics or Computer Science, for example, with a bachelor's degree or a license (French undergraduate degree) in a relevant field. 

  • Students with a limited background in Mathematics or Computer Science and students who do not meet the proficiency requirements in English (a Toefl ITP 520 or iBT score 60 will be requested) can apply, but will be encouraged to take additional preparatory steps before starting the program.

  • Students who cannot attend the program on-site (for example, because of work commitments or for medical reasons) are able to apply for the online program. However, these students should note that a certain period of attendance is mandatory each semester.

  • Students with a strong background in Mathematics and Computer Science (from other programs) may apply for  second-year parallel admission (opening Fall 2019). A selection committee will study the viability of such a proposal.

  • Students are expected to be curious and open-minded, especially regarding the different fields of application of Data Science.

 

How to apply

  • The application process is online
  • Be prepared to upload documents such as a recent picture of you, a copy of your passport, your transcripts, your english proficiency certificate (Toefl or equivalent) if not native speaker, a resume (CV), a motivation letter, academic and/or professional reference letters (facultative)...
  • We will also ask you to prepare a Data Science project proposal, describing a project in Data Science that you would like to do during the first year (the project can be illustrated with some data and a minimal workflow process).
  • Let's start your online application (you will have to click on "E-candidatures for masters").

Selection committee dates

There will be 3 meetings of the selection committee :

  • mid-March 2019,
  • mid-May 2019,
  • early July 2019.

  

Contact informations

Nice

 

 - Scientific board - 

The UCA Data Science master benefits from the scientific expertise of its executive board, which is mainly composed of Mathematics and Computer Science professors. Pr. Charles Bouveyron is heading the MSc Data Science & AI.

 - Location - 

 The master Data Science & AI will be held at the Campus Lucioles, Biot. Some courses may be held in Campus Valrose or Campus SophiaTech 

- Contact - 

You can reach us by sending an email at

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Staff

Pr. Charles Bouveyron

Director of the MSc “Data Science & AI” 

Charles, is Professor of applied mathematics (statistics and AI) at Université Côte d’Azur in Nice France, and holds the Chair Inria in Data Sciences. He is research fellow and associate director at the Institut 3IA Côte d’Azur.

Member of the laboratoire J.A. Dieudonné, UMR CNRS 7135, and of the team Epione in INRIA Sophia-Antipolis. He is also associate editor for The Annals of Applied Statistics and the founding organizer of the series of Statlearn workshops.

His research interests include statistical learning (clustering, classification, regression) in high dimensions, adaptive statistical learning (uncertain labels, evolving distributions, novelty detection). Statistical learning on networks, functional data and heterogeneous data and applications of statistical learning (medicine, image analysis, chemometrics, humanities, ...).

 

 Pr. Frédéric Precioso

Responsible for the second year of MSc "Data Science & AI"

Frédéric is currently the Artificial Intelligence programme responsible for the National Research Agency (ANR) at State Investment Programmes Division and Digital Technology and Mathematics Dept.

He is Professor at the University Côte d'Azur, lecturer at the École d'ingénieur Polytech'Nice Sophia, member of the SPARKS (Scalable and Pervasive softwARe and Knowledge Systems) team of the I3S UMR 7271 CNRS-UNS laboratory. He is responsible of the research group MinD (Mining Data).

His main research interests are: (i) Understanding Deep Learning (Active Learning, Bio-inspired optimization and interpretation, Deep Natural Language Processing vs Statistical Text Analysis, Deep Learning and Knowledge, Embedded Deep Learning); (ii) Understanding Inhomogeneity (Semantics from 3D, Semantics from video and from multimedia data, Semantics from the gaze, Semantics in the time series); (iii) Meta-Learning/Meta-Mining (AI on-demand Platform, Multi-Consensus Clustering, Hybridization Machine Learning – Evolutionary algorithms.

Project Manager

Noelia is a sociologist specialized in Research administration and dissemination of knowledge from the Ecole Normale Superieure de Lyon. She has managed with care, several international projects at different unversities in Lyon involving international students and researchers. She has joined the team to manage and develop the MSc Data Science & AI.

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