A hybrid pathway focused on big data, connected systems and intelligent services.
The Master of Science in Engineering DSC programme trains engineers and computer scientists capable of mastering the entire digital chain, from raw data to interconnected intelligent systems.
The curriculum combines advanced computing, data science, distributed architectures, embedded systems/IoT and interfacing with modern web services.
The programme is taught half in French and half in English, reflecting its international ambition.
General Structure of the Curriculum
The curriculum is based on two years of instruction (M1/M2 or direct entry into M2 depending on profile), structured into thematic blocks:
- Fundamentals of Digital Systems
- Software Architectures and Web Services
- Big Data, BI and Decision Support
- Internet of Things and Connected Systems
- System and Data Security
- Cloud, Edge Computing and Distributed Systems
- Supervised Project and Professional Placement
Detailed Content of Teaching Units (UE)
UE 1 — Data & Business Intelligence
Acquire essential skills to structure, exploit and analyze big data.
Key Concepts
- Data Modeling
- Advanced Databases
- Data Warehouses
- Decision Support & BI Tools
- Knowledge Extraction
- Introduction to Big Data
Objective
Learn to transform data into actionable information for intelligent systems or decision support dashboards.
UE 2 — Programming and Software Architectures
Build robust, modular and distributed applications.
Content
- Advanced Programming (Java/Python depending on modules)
- Service-Oriented Development
- APIs, REST, Microservices
- Software Design Methods
- Continuous Integration, Software Quality
Objective
Master modern software development techniques for connected environments.
UE 3 — Internet of Things & Connected Systems
Develop and interconnect communicating objects.
Content
- IoT Architectures
- Protocols (MQTT, CoAP, LoRa, BLE…)
- Embedded Systems
- Sensors, Gateways, Cloud Integration
- IoT Security
Objective
Understand the complete chain of an IoT system, from sensor to associated digital service.
UE 4 — Cloud & Distributed Systems / Edge Computing
Deploy scalable applications in modern architectures.
Content
- Cloud and Edge Paradigms
- Virtualization and Containers
- Orchestration (Docker, Kubernetes)
- Distributed Processing
- Service Infrastructures
Objective
Design and manage robust, elastic and interconnected systems.
UE 5 — Artificial Intelligence & Intelligent Systems
Introduce analysis and decision-making capabilities.
Content
- Basic Machine Learning
- Data Modeling
- Intelligent Systems for Complex Environments
- Embedded AI / Distributed AI
Objective
Understand how to integrate AI into connected services and distributed systems.
UE 6 — System & Data Security
Ensure confidentiality, integrity and robustness of systems.
Content
- Network Architecture Cybersecurity
- Software Vulnerabilities
- Communication Security
- Identity Management
- Secure Development Practices
Objective
Integrate security from the design phase, particularly in IoT or complex web environments.
UE 7 — Project, Internship and Research
An essential practical component.
Includes
- Supervised long-term project (complete development of a connected system or data/IoT prototype)
- Internship or work-study programme depending on chosen modality
- Dissertation and Defense
Objective
Apply skills to a real case, in industry or research.
Teaching Methods
- Lectures and Tutorials in French/English
- Intensive Practical Work
- Agile Projects, Collaborative Development
- Hands-on Experience in IoT/Cloud Environments
- Industrial Case Studies
Skills Acquired upon Completion of the Master of Science in Engineering DSC
Graduates are able to:
- Develop modern distributed applications
- Design and integrate connected systems (IoT)
- Exploit large data volumes
- Secure digital services
- Orchestrate Cloud/Edge architectures
- Analyze and leverage data in intelligent systems
Pedagogy and Specific Options
- Research-Based Pedagogy
The programme benefits from the expertise of the LIMOS (CNRS) and LIS laboratories. Learning is centered on solving real problems through intensive projects. - Bilingual Curriculum
Approximately half of the modules are taught in English, ensuring graduates have professional fluency in international contexts. - Work-Study Option Available in M2
- The Master of Science in Engineering DSC is also available as a work-study programme at M2 level, offering complete professional immersion and funded training.
🔗 Syllabus
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Programme Director
Administrative contact
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