Major Data Sciences

Degree

Engineering degree (Bac+5)

Campus

Montpellier

Access

Bac+4

Timing

Alternation

Full time

Language

English

Internship

2 semestres

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The aim of the Data Sciences major is to train flexible and adaptable engineers both strong in Mathematics & Computer Sciences. They will be able to help companies and laboratories to structure their data and to produce new insights with Data analysis and Machine Learning approaches. Emphasis is placed on a systemic approach (cost/benefit) including legal, human, economic and environmental aspects.

Combining their generalist education with an expertise on all the Data Journey, the graduates will be able to addressall the missions of the Data Analyst: data recovery, structuration, analysis & reporting, in direct interaction with the enduser. They will also have a strong suit in Artificial Intelligence and Machine Learning allowing them to create models and advanced tools (predicter, classifier, etc.) and in Data Engineering, enabling them to collaboratively develop services using a v lue-driven, short-cycle approach and then deploy these services in the enterprise IT architectures.

Students have the option of completing the Major cycle (4th and 5th year) as an apprentice, thanks to the FISEA program. (Initial training under apprentice student status).

Program structure

The major extends over two academic years and is organised around two inclass semesters, framed by two internship semesters. (note: for the international students, the first internship is replaced by an International Project semester which includes mechanics, energy, computer science and French).

All the CUs are offered in English. They are designed as independent credits so as to admit students from other programs or students attending vocational training.

In order to be as close as possible to employment conditions, the Major's project CU use a project approach, thus confronting students to a real client specifications, teamwork and autonomy.

Compulsory CUS:

Computer science
Data architecture
Exploratory Data Analysis
Basics of Machine Learning
Support Digital Transformation
Major’s project

Compulsory CUS:

Data diversity
Machine Learning: Theory & Practice
Responsible Data Science
Data Strategy
Major’s project

Elective CUS*:

Deeper into Data Science
Deeper into Data Engineering

*One of the two ELECTIVE CUS must be chosen. Opening of the elective is subject to a minimal number of student.

Projects

A project is carried out during both academic semesters in collaboration with a company. It is used as a guideline for the whole semester and serves as support to many lectures. Some examples of projects conducted in the major:

4th year

Development of a full data pipeline (collection, storage, dashboard) to produce insights for various clients (software dev., department administration, water authority...)
Development of web tools / APIs to allow access to large datasets and their analysis (legal documentation, aerospace databases...)

5th year

Train a Computer Vision Machine Learning model to automatically extract quantitative information (size, number,location) of objects for various application (Marine life, Land use, Petri dishes...)
Model complex systems with Machine Learning to predict behavior in various contexts (Heat system optimization, Failure detection of sensors, user profiling...)