ORGANIZATION AND FACULTY (ADEO)

Master in Big Data

ORGANIZATION

 

2 years full time, 120 ECTS

Language of instruction: English

The 3 pillars of the ADEO Master:

  • Modeling, operational research and decision support
  • Data exploration and data mining
  • Business Intelligence

 

M1 Program: from September to June (60 ECTS, 611 h)

The M1 provides the fundamental tools in Computer Science and Mathematics necessary for the M2. It is based on the three pillars characteristic to this master. As well as the fundamentals, students will be taught the essential elements of project management. This first year will culminate in a large transversal team project. The M1 is divided into two semesters. Each semester is worth 30 ECTS.

Download Syllabus M1

 

Data exploration

  • Inferential Statistics (3 ECTS, 30h, 1 S*)
  • Data Analysis (2 ECTS, 2h, 1 S)

 

Mathematics for Computer science

  • Partial Differential Equations and Finite Differences (3 ECTS, 30h, 1 S)
  • Operational Research: Linear Optimization (2 ECTS, 20h, 1 S)
  • Combinatory Optimization (2 ECTS, 18h, 1 S)
  • Complexity theory (1 ECTS, 9h, 1 S)
  • Simulation and Stochastic Process (3 ECTS, 30h, 2 S**)
  • Introduction to Predictive Modelling (2ECTS, 21h, 2 S)
  • Deterministic and Stochastic Optimization (3 ECTS, 30h, 2 S)
  • Introduction to Data Mining (2 ECTS, 21h, 2 S)

 

Software and Architecture

  • Object-Oriented Modelling (OOM) with UML (3 ECTS, 30h, 1 S)
  • Object-Oriented Design and Programming with Java (2 ECTS, 30h, 1 S)
  • Relational Database: Modelling and Design (3ECTS, 30h, 1 S)
  • PLSQL (2 ECTS, 21h, 2 S)
  • Architecture and Network Programming (3 ECTS, 30h, 2 S)
  • Parallel Programming (3 ECTS, 30h, 2 S)

 

Engineering Science

  • Signal and System (3 ECTS, 21 h, 1 S)
  • Signal processing (3 ECTS, 30h, 1 S)

 

Research Initiation

  • Scientific Paper review (1 ECTS, 9h, 1 S)
  • Final research project on BIG DATA (5 ECTS, 50h, 2 S)

 

Project Management

  • AGIL Methods & Transverse Project (2 ECTS, 21h, 2 S)

 

Languages an other courses

  • French and Foreign languages (6 ECTS, 61h, 1&2 S)
  • Personal and Professional Project (1 ECTS, 15, 1 S)

*1 S= 1st semester,  ** 2 S= 2nd semester

 

M2 Program: from September to September (60 ECTS, 641h)

The M2 is, like the M1, based on the three pillars of the master, except at a higher level of expertise. To train experts in our field, we provide the students with professional skills in modelling, design and implementation of computer architecture, data mining and optimisation.

M2 level is a collection of modules, giving in total 60 ECTS (42 ECTS for the modules taught from September to April, plus 9 ECTS for the internship and 9 ECTS for the Master thesis).

Download Syllabus M2

 

Computer technologies

  • Web Services (3 ECTS, 24h, 1 S)
  • NOSQL (2 ECTS, 20h, 1 S)
  • Java EE (3 ECTS, 24, 1S)

 

Data exploration

  • Semantic web and Ontology (2 ECTS, 20h, 1 S)
  • Data mining: application (2 ECTS, 20h, 1S)
  • Social Network Analysis (2ECTS, 18h, 1S)
  • Collective intelligence: Web Mining and Multimedia indexation (2 ECTS, 20h, 2 S)
  • Enterprise Miner SAS (2 ECTS, 20h, 2 S)
  • Text Mining and natural language (2 ECTS, 20h, 2 S)

 

Operations Research

  • Thorough operational research: modelling and business application (2 ECTS, 21h, 1 S)
  • Game theory (1 ECTS, 10h, 1 S)
  • Forecasting models (2 ECTS, 20h, 1 S)
  • Constraint programming (2 ECTS, 20h, 2 S)
  • Multi-objective and multi-criteria optimisation (2 ECTS, 20h, 2 S)
  • SAS OR (2 ECTS, 20h, 2 S)

 

Research Initiation Initiative

  • Scientific Paper review (1 ECTS, 10h, 1 S)
  • Final research project on BIG DATA (2 ECTS, 39, 2 S)

 

BI Architecture

  • BI Theory (2 ECTS, 20h, 2 S)
  • BI Practice (2 ECTS, 20h, 2 S)

 

Languages and workshops (4 ECTS, 105h, 1&2 S)

  • French as a Foreign language
  • CV workshop
  • Personal and Professional Project

 

Internship

  • Internship (9 ECTS, 22 weeks minimum)

 

Thesis

  • Master thesis (9 ECTS, 150h)

Internship

The Master in Business Analytics requires students to complete an internship of minimum 22 weeks.  This professional experience, in complement to the academic skills acquired in the program, is part of the degree requirements and it is essential to the student’s future career. The main objective of the Internships is to ensure a practical application of the instruction given in the program.

The internship assignment is established by mutual consent of the Company, the Student and the EISTI. There needs to be at least 3 meetings with the intern, the referent and the person in charge in the company/research laboratory. Each meeting will lead to a (professional) presentation by the intern which will end in an evaluation.

As well as these meetings, the student will have to write up an internship report containing:

  • The presentation of the company/laboratory
  • The presentation of the mission
  • The analysis and synthesis of the work undertaken
  • A personal analysis of the internship: what worked and what didn’t.

 

EISTI career center provides different services to assist students in their internship/job research:

  • Career Fairs
  • EISTI ALUMNI meetings
  • CV/cover letter /interview workshops
  • Business conferences with guest speakers
  • Job/internship search tools

 

Teaching

All the classes will be taught in English except:

  • FLE (French as Foreign Language), where the objective is to teach the students how to understand and express themselves in French.
  • Cultural Openness, where the objective is to enrich the students’ knowledge of French culture.

Non-French speakers will be asked to participate to one week intensive French course that precedes the start of the program and allows students to gain the linguistic knowledge necessary for daily interactions

 

E-Learning area

The EISTI offers an e-learning site to all its students, which complements everything the students will learn through their presence and participation in class:

  • Class documents, practical work and tutorials online,
  • Questions and discussions between teachers and students, and among students,
  • A possibility of handing work in online.

All Master’s students are equipped with a laptop for the duration of the program that remains the property of the EISTI.

 

FACULTY

 

  • Rushed Kanawati
  • Grégoire de Lassence (SAS)
  • Stéphane Le Ménec (Docteur Ingénieur, chercheur Matra Défense)
  • Hervé de Milleville
  • Antonios Tsourdos (Professeur université de Cranfield GB)
  • Guy Almouzni (EISTI)
  • Rachid Chelouah (EISTI)
  • Matthias Colin (EISTI)
  • Abdel El Janati (EISTI)
  • Jean-Paul Forest (EISTI)
  • Irina Kortchemski (EISTI)
  • Péio Loubière (EISTI)
  • Maria Malek (EISTI)
  • Marietta Manolessou (EISTI)
  • Houcine Senoussi (EISTI)
  • Patrick Siarry (Professeur des universités à Paris Est)
  • Jean-Paul Vedel (EISTI)