# ENSAM x DSTI Digital Industry & AI. Canonical HTML: https://dsti.school/ensam-dsti-digital-industry-ai This Markdown copy is generated from the same DSTI static-site build as the canonical HTML page. It is intended for machine readability and concise retrieval. ENSAM x DSTI • Joint postgraduate programme • Digital Industry & AI A one-year postgraduate programme for engineering graduates — especially early-career engineers — who want to add data, AI, cloud, cyber security, visualisation and digital twins to an industrial engineering background. The programme is built as a part-time, weeks-on / weeks-off route, with applied projects and a final internship. Applications are submitted through the ENSAM platform. Apply through ENSAM Speak with DSTI View criteria 1 year Postgraduate specialisation, part-time rhythm. 120 ECTS Master-level programme • RNCP level 7 English B2 Required for non-native speakers. Intake Autumn · October Rhythm Part-time weeks-on / weeks-off Locations Paris · Sophia-Antipolis · Bordeaux-Talence · Live Streamed in France 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. Positioning ### 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. Target profile ### Engineering graduates Recently graduated engineers, industrial generalist engineers or equivalent university profiles in engineering. Objective ### Complementary competences Add data, AI, cloud, cyber security, visualisation and digital twins to an initial engineering education. Professionalisation ### 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. Solution definition ### Define solutions Frame needs, data, algorithms, interfaces and assessment criteria for an AI solution adapted to industry. Data management ### Structure information Understand acquisition, databases, quality, governance and security of industrial data. Processing & AI ### Evaluate models Apply, interpret and critique data processing, machine learning and optimisation methods. Digital twins ### 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. ECTS 120 Master-level programme • RNCP level 7. Indicative rhythm 2 / 3 2 weeks of study, 3 weeks away from class. Experience Internship Final internship, complemented by applied projects. Intake Autumn October 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 campus DSTI Paris ### Academic and industrial capital A dense environment for companies, engineering, consulting, data and innovation. Sophia-Antipolis ### Technology ecosystem DSTI’s French Riviera campus is located in Europe’s first science and technology park. Live Streamed ### 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. Data Engineering ### 29h Big vs Smart Data, reporting, visualisation and preparation for Microsoft Power BI. Artificial Intelligence and Machine Learning ### 101h Python Machine Learning Labs, time series, neural networks, model reduction and hybridisation. Statistics and Applied Mathematics ### 51h Statistics, probability, optimisation and numerical simulation. Cyber Security ### 25h Security principles, design patterns, encryption, code safety and system protection. Infrastructure and Communication ### 132h SQL, AWS, inter-system communication, Industrial Digital Twins, Virtual Reality and Augmented Reality. Projects ### 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 page Microsoft ### Exam PL-300: Microsoft Certified: Power BI Data Analyst Associate Prepared through reporting, visualisation and data-engineering coursework. Official certification page ### Learning 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. LinkedIn 08 — 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. Academic profile ### Engineering degree or equivalent The programme is aimed at engineering graduates and equivalent university profiles in engineering, preferably industrial engineering. Language ### B2 English This level is required for non-native speakers so they can follow classes, contribute to projects and complete the programme successfully. Part-time format ### Administrative compatibility The format requires a situation compatible with a weeks-on / weeks-off study rhythm and a final internship in France. Application ### ENSAM platform The official application is submitted through the ENSAM system. Open ENSAM platform 09 — 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. Apply through ENSAM Book a meeting On this page