Master of Science in Statistics for Smart Data

Ensai (The National School for Statistics and Data Analysis)Bruz - FRANCE

Field(s) of study: Big Data
Cost of pre-eligibility application: 
  • Via Mastersbooking: 0 €
  • Via the regular school procedure: 100 €
Course cost: 8 000 €
Possible funding options: 
  • Bank loan
  • Paid internship
  • Payment by a training organisation/Training Leave
  • Payment by my company
  • Personal or family funding

Next admission round: 

Next recruitment session:
Jan 2017
to
May 2017

Available slots: 

Available spots: : 18
Places available per academic year: 18

Course length: 

1 year (12 months)

Start of the program: 

September 2017

Level of entry: 

A Level+4 years
A Level+5 years

Accreditations

ECTS

Our MSc , taught entirely in English, is oriented towards the new challenges of modeling and analyzing massive amounts of data. Numerous Big Data programs have surfaced in the recent past, most of which are highly IT-oriented. ENSAI has chosen to go a different route. While students learn not only the latest in technological know-how, they more importantly master the statistical and mathematical skills we believe are essential to becoming successful, skilled data scientists.

Students will learn the methodological aspects and the practical skills needed to become a Data Scientist, acquire the core concepts of data management, the necessary tools to access, handle, and analyze massive amounts of heterogeneous data. They will master the mathematical models and algorithms vital for rapidly extracting information from data and develop knowledge  for deep understanding of data.
 
Statistical Models for Dependent Data
Nonhomogeneous Markov Chains
Graphical Networks & Dynamic Networks
Dynamic Data Visualization
 
Machine Learning
Features Selection & Regularization Methods 
Deep Learning
Parallel Computing with R & Python
 
Smart Sensing
Smart Sensing Foundations
Applications of Smart Sensing
 
Models for Complex Data
High-Dimension Time Series
Functional Data with Applications
 
IT Tools
IT Tools 1 (Hadoop, NoSQL, Spark)
IT Tools 2 (GNU Linux, Shell Scripting, Cloud Computing)
 
Challenges for Smart Society
Energy Transitions: Quantitative Aspects
Smart Data Project
Professional Lecture Series

Course format: 

The program is divided into two semesters:

  • From September to February:  coursework in English at ENSAI
  • Starting end of February: a 4 to 6-month internship followed by final report and jury defense     

Qualifications/expertise after completing the program

Graduates of the program are skilled Data Scientists. In addition to doctoral possibilities in research, graduates have numerous career opportunities in international corporations and data start-ups in many fields including:

  • Business Analytics
  • Internet of Things
  • Personalized Medicine
  • Smart Grid Optimization
  • Smart Society
  • Social Networks Analysis
  • Supply Chain Optimization

Entry requirements

Bac +4: Ideal candidates who wish to enter this M2-level program (Bac +5) must have completed a minimum of four years of higher education (at least a 4-year Bachelor's degree or the first year of a Master's).
A strong statistical, mathematical and computer science background is necessary. A list of expected and recommended prerequisites can be found on the Statistics for Smart Data page - Admission requirements of the ENSAI website.
 

Admission criteria: 

All candidates must apply online on the ENSAI website www.ensai.frAdmission,  MSc in Statistics for Smart Data. Paper applications will not be accepted.
The application process is three-fold:

  • Successful submission of the official online Application Form
  • Successful submission of mandatory application documents (CV in English, statement of purpose, copies of degrees & diplomas, grade transcripts, English language certificate, French language certificate, GRE or equivalent, Academic or professional references, application fees…)
  • A personal interview will be organized for some candidates based on the quality of their application

Manager: 

Mrs/Ms Cécile TERRIEN