Formation

Majeure Data engineering

Accès

Bac+4

Campus

Montpellier

Diplôme

Diplôme d'ingénieur (Bac+5)

Langue

Anglais

Stage

2 semestres

Rythme

Plein temps

Télécharger la brochure

Formations

The aim of the Data Engineering 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 address all the missions of the Data Analyst: data recovery, structuration, analysis & reporting, in direct interaction with the end-user but will also have a strong suit in Data Science allowing them to create models and advanced tools (predicter, classifier, etc.) and suffi cient knowledge on the Data Engineering side to collaborate on the actual transformation of those models into services.

With a pedagogical approach based on skills, learning-by-doing and life-long learning the graduates should be able to integrate small and big structures and to adapt to many different business.

Télécharger la brochure

Nous rencontrer

Nous soutenir

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

4^th year:
- Development of a web tool allowing the co-design between volunteers and researchers of a common OLAP-cube representation of a biodiversity database.
- Data structuration (model & tools) of a financial analysis process in renewable energy sector.
5^th year:
- Use of Natural Language Processing techniques for the analysis and clustering of a large medical's survey database.
- Development of Deep Learning tools for Object detection in aerial imagery applied on ecological study of cetaceans.