The “Computer Science and Electronics for Data Engineering” apprentice-status engineering program is designed to meet the growing needs of the data processing industry, from data capture and visualization to software architecture, connected objects and artificial intelligence. responds to the growing needs of manufacturers in the data processing sector, from data capture and visualization to software architectures, connected objects and artificial intelligence.
Passionate about BigData? Become an expert in data and data security, from data capture to data processing.
Digital transformation leads to the creation of billions of pieces of information that are captured, recorded, processed and then used to monitor, improve and innovate any process.
The “Computer Science and Electronics for Data Engineering” course is designed to meet the challenges of industry and digital services, where complex problems involving the design and development of dedicated applications embedded on electronic platforms or deployed in the cloud are paving the way for countless innovative applications.
Training program
Theoretical tools for data engineering
Mathematical techniques and numerical tools for data analysis
Probability and statistics for data analysis and engineering
Digital legislation and data analysis issues
Data processing, analysis and exploitation
Data management and visualization: Architecture
relational and interactive design
Algorithms & Data structures (C language)
Infrastructures, architectures and embedded systems for data management
System, OS and components for embedded systems
Electronics: instrumentation and data capture
Telecommunications chains
Innovation projects
Societal issues
Project management
Communication
Digital sustainability and eco-design
Innovation project: Technical specifications
Technology watch and introduction to research
Apprenticeship
Work-study programs
Apprenticeship
Apprenticeship master’s day
Year 1 defense
Language skills
English language skills
Fundamentals of data engineering
Inferential statistics
Network management and data backup solutions
Software engineering and Git : Versioning techniques and OOP in Java
Data processing, analysis and exploitation
Information systems and data management
Data Analysis and Visualization with Machine Learning
Sociology and Digital Data Management: From Analysis to Textual Data
Infrastructures, architectures and embedded systems for datamanagement
C development and lifecycle management of embedded systems
Transmission physics
Engineering of embedded systems and their communicating environments
Innovation projects
Creativity techniques
Ecodesign of digital systems and components: life cycle
Innovation project: prototype
Project management
Multidisciplinary workshop
Innovation
Apprenticeship
On-the-job training periods
Apprenticeship
Year 2 defence
Language skills
English language skills
Fundamentals of data engineering
Methods and numerical computation for data engineering
Software engineering
Digital transition
Cloud Computing and NoSQL technologies for Big Data
Distributed applications
Data processing, analysis and exploitation
Deep learning
Multimodal data mining and management
Full-Stack Web and data services
Infrastructures, architectures and embedded systems for datamanagement
Embedded and multitasking systems: Real-time design and multithreading
Embedded applications and cross-compilation
Securing data exchanges and data
IoT
Innovation projects
Economics of innovation
Financial management
Innovation project: revenue
Adding value to a transition project
Research approach
Apprenticeship
Work-study periods in companies
Skills assessment
Year 3 defence
Company management: feedback
Employment law
Self Marketing
Language skills
English language skills
Fields of application
Industry of the future, logistics, healthcare, banking/finance/insurance, transport, energy, e-commerce, telecoms, consulting, social networks, open data and government data, astronomy, home automation, Smartgrid.
Career opportunities
Data engineer
Data/big data engineer
Information Systems Architect Engineer
Data analysis engineer
Project engineer
Artificial Intelligence Engineer
Admissions
Conditions:
You are under 30 and have completed one of the following training courses:
- CPGE
- GOAL 2 / GOAL 3 (RT, GEII, SD, IT)
- Scientific BTS
- Professional license
- L2 or L3 validated
Admission to the 1st year of the apprenticeship engineering program in Computer Science and Electronics for Data Engineering is by competitive examination.
Registration :
Télécom Saint-Étienne shares its apprenticeship recruitment with the Institut Mines-Télécom schools. You must therefore submit an application on the Institut Mines-Télécom apprenticeship platform.
The platform will be open from February 3 to March 11, 2025.
Admission:
If you are pre-admitted to our school, you will then be invited to take tests on our premises on April 12, 2025:- 45-minute written test (aptitude and English tests)
- Motivational interview with a panel of judges comprising a teacher-researcher from the school and a Télécom Saint-Étienne graduate.
You will be notified of your eligibility results on April 15, 2025. Admission will take place once the apprenticeship contract has been signed.
Apprentices' tasks at the company
Because it’s our apprentices who say it best, use the posters below to find out how they progressed in their companies, the different assignments they were given and the skills they acquired over the 3 years of their training.
Discover the apprentices' posters
Testimonials
Kent’s video testimonial
Companies hosting our apprentices
