Industry 4.0, data and AI, with real engineering culture.
As industries combine data, automation, AI and connected systems, engineers need to specify, integrate and manage digital solutions without losing sight of physical and industrial systems.
01 — Programme identity
A specialisation bridge for industrial engineers.
The programme combines the industrial heritage of Arts et Métiers with DSTI’s expertise in data, AI and digital systems. Founded in 1780, Arts et Métiers is France’s second-oldest industrial engineering school; DSTI adds a specialist data, AI, cloud and cyber security environment.
Engineering graduates
Recently graduated engineers, industrial generalist engineers or equivalent university profiles in engineering.
Complementary competences
Add data, AI, cloud, cyber security, visualisation and digital twins to an initial engineering education.
Part-time rhythm and final internship
Weeks on / weeks off, applied projects and a final internship connect the coursework to real industrial situations.
02 — Learning objectives
Design, analyse and deploy industrial digital solutions.
The specialisation gives engineers an operational reading of data, AI and digital infrastructures applied to complex industrial environments.
Define solutions
Frame needs, data, algorithms, interfaces and assessment criteria for an AI solution adapted to industry.
Structure information
Understand acquisition, databases, quality, governance and security of industrial data.
Evaluate models
Apply, interpret and critique data processing, machine learning and optimisation methods.
Supervise deployment
Explain, design and support digital twins to improve operations and decisions.
03 — Structure & rhythm
One year, part-time.
The rhythm combines teaching weeks, weeks away from class, practical work, projects, certification preparation and a final internship. It is designed for candidates who already hold an engineering degree or equivalent engineering background.
ECTS120Master-level programme • RNCP level 7.
Indicative rhythm2 / 32 weeks of study, 3 weeks away from class.
ExperienceInternshipFinal internship, complemented by applied projects.
IntakeAutumnOctober start.
Teaching language
The programme requires B2 English for non-native applicants. Teaching is delivered in English; project work and the final internship in France are reviewed with the programme teams according to each candidate’s situation.
04 — Locations & formats
A programme rooted in French industrial ecosystems.
Students may be based in Paris, Sophia-Antipolis or on the ENSAM Bordeaux-Talence campus. Live Streamed access may be possible in France only, depending on academic and organisational compatibility.
ENSAM Bordeaux-Talence
An Arts et Métiers campus at the heart of industrial engineering.
The Bordeaux-Talence campus complements DSTI’s Paris and Sophia-Antipolis anchors for this joint programme.
Discover Bordeaux-Talence campusAcademic and industrial capital
A dense environment for companies, engineering, consulting, data and innovation.
Technology ecosystem
DSTI’s French Riviera campus is located in Europe’s first science and technology park.
France only
Live remote attendance may be possible for students already based in France.
05 — Curriculum
Data, AI, infrastructure and industrial systems.
The curriculum covers the building blocks needed to move from data analysis to the integration of digital solutions in industrial environments.
29h
Big vs Smart Data, reporting, visualisation and preparation for Microsoft Power BI.
101h
Python Machine Learning Labs, time series, neural networks, model reduction and hybridisation.
51h
Statistics, probability, optimisation and numerical simulation.
25h
Security principles, design patterns, encryption, code safety and system protection.
132h
SQL, AWS, inter-system communication, Industrial Digital Twins, Virtual Reality and Augmented Reality.
90h
Practical projects around ML models, visualisation, secure infrastructures and industrial-process optimisation.
06 — Certification preparation
Certification preparation as a professional plus.
The programme prepares students for two widely recognised external certifications, but neither certification is required to graduate. The value is positive and practical: students can use the preparation to strengthen their profile in cloud architecture, reporting and visualisation.
Prepared, not mandatory
AWS and Power BI preparation reinforce the industrial digital pathway.
Certification preparation is embedded in relevant coursework. Students may choose to sit the external exams when it supports their project, but graduation remains based on the academic programme, projects and final internship.
Prepared in the programme AWS Certified Solutions Architect – Associate and Exam PL-300: Microsoft Certified: Power BI Data Analyst Associate.
No graduation requirement These external certifications are not mandatory for graduation.
Professional signal They can still be a useful employability signal for cloud, data analytics and industrial digital-transformation roles.
Amazon Web Services
AWS Certified Solutions Architect – Associate
Prepared through cloud, infrastructure and systems-integration coursework.
Official certification pageMicrosoft
Exam PL-300: Microsoft Certified: Power BI Data Analyst Associate
Prepared through reporting, visualisation and data-engineering coursework.
Official certification pageLearning resources and technical environments
Students also benefit from DSTI’s learning ecosystem, including DSTI Learn, AWS Academy, Microsoft Learn for Educators, Microsoft Azure for Education, O’Reilly and dedicated technical environments where relevant.
07 — Programme co-direction
Co-directed by ENSAM x DSTI.
The programme leadership combines industrial systems knowledge, engineering science and specialist teaching in data, AI and digital infrastructures.
Programme co-director
Sébastien Corniglion
Chief Executive Officer of DSTI School of Engineering, information-systems engineer and teacher in data, information systems and digital infrastructures.
LinkedIn
Programme co-director
Pr Emmanuelle Abisset-Chavanne
Professor at Arts et Métiers, specialist in engineering science and modelling for advanced industrial environments.
LinkedIn08 — Admissions & application
Applications are submitted through the ENSAM platform.
The programme is selective. Applications are submitted and followed through the ENSAM system, with review of academic background, project fit and language prerequisites.
Engineering degree or equivalent
The programme is aimed at engineering graduates and equivalent university profiles in engineering, preferably industrial engineering.
B2 English
This level is required for non-native speakers so they can follow classes, contribute to projects and complete the programme successfully.
Administrative compatibility
The format requires a situation compatible with a weeks-on / weeks-off study rhythm and a final internship in France.
ENSAM platform
The official application is submitted through the ENSAM system.
Open ENSAM platform09 — Careers
Roles at the interface of industry and digital systems.
Graduates can target roles linked to industrial AI, industrial digital systems, digital twins, cloud, data and digital transformation.
Industrial Data Scientist
Machine Learning Engineer
Digital Transformation Consultant
Cloud Solutions Architect
Digital Twins Engineer
Industry 4.0 Project Manager
Next step
Apply to the ENSAM x DSTI programme.
If your profile matches a postgraduate specialisation after an engineering degree or equivalent background, start with the ENSAM platform or speak with DSTI to check your project.