Formation

Majeure Data engineering

Accès
Bac+4
Campus
Diplôme
Diplôme d'ingénieur (Bac+5)
Langue
Anglais
Stage
2 semestres
Rythme
Plein temps
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.

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*:

  • Toward Machine Learning Engineer
  • Toward Data Engineer

*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:

  • 4th 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.
  • 5th 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.

 

Training conditions

Duration: two years

Location: EPF campus de Montpellier

Tuition fees for the 2024-2025 year: 9 640€

36 students per year

Career & opportunities

  • Companies in the digital industry
  • Insurance and health companies
  • Banks/Financial industry
  • Sales, distribution/Marketing
  • Medical/pharmaceutical industry
  • Energy
  • Communal services
  • Industry
  • Transport industry
  • Life sciences
  • Natural Sciences
  • Engineering
  • Journalism

  • Data Analyst
  • Data Scientist
  • ML Data Engineer

And many other position in the IT and Data sector.

Contact

Image
gademerantoine
Antoine GADEMER
Co-responsable de la majeure Data Engineering
Contacter
Robert RAPADAMNABA
Co-responsable de la majeure Data Engineering
Contacter