• Language of instruction – English (B2 level required)
  • Mode of learning – daytime, full time, on-site and remote classes.
  • Length – M1: 1 year; M2: 1 year; M1+M2: 2 years.
  • Official title appearing in the degree:
    • Master Sciences, Technologies, Santé – Mention Informatique, parcours en anglais Artificial Intelligence for Connected Industries
    • meaning Master of Science, Technologies and Health – speciality in Computer Science, track in Artificial Intelligence for Connected Industries
  • Teaching period: mid September to beginning of June.
  • Master code: MR11601D
  • Chair: Stefano Secci, Cnam.
  • Contact: master-roc@cnam.fr 
  • 2024/2025 calendar: from Sept 21 to May 31 (remedial exams until end of June).
M1 (first year) courses. Paris site.
M2 (second year) courses. Paris site.

More details on the Mulhouse teaching site – apprenticeship deployment (in Grench and English) of the AI4CI master at this webpage.

Next we provide a synthetic description of each teaching module with the links to the detailed course program.

M1 – Semestrial Core Courses

Introduction to AIML for Connected Systems

Teacher: Pedro Braconnot Velloso (Cnam)

Advanced course on artificial intelligence and machine learning algorithms, with their application to real data coming from IP, industrial and mobile networks and computing infrastructures.

Operations Research and Network Optimization

Teacher: Safia Kedad-Sidoum (Cnam), Cristina Cervello Pastor (UPC)

Basics on combinatorial optimization, graph theory, complexity, and network optimization problem modeling.

Network Architecture

Teacher: Stefano Secci (Cnam)

Basics on communication network principles, focused on layers 2 (data-link) and 3 (network).

Operating Systems and Computer Architecture

Teacher: Sami Taktak (Cnam)

Introduction to computer architectures and operating systems, with a particular focus on IoT devices and systems.

Network Security

Teacher: Nicolas Pioch (Cnam)

Course on network security, with a particular focus on novel cybersecurity threats and principles of cryptography.

Contemporary Economic Issues

Teacher: Elisa Darret (Cnam)

Inter-disciplinary course on bases on contemporary economics and financial system dynamics.

Automatics

Teacher: Jéremy Van Gorp (Cnam), Birte Glimm (UULM)

Basics in Automatic Control for Industrial Connected Systems.

Distributed and Federated Learning

Teacher: Stefano Secci (Cnam), Francesco De Pellegrini (AU)

Advanced courses on methods to decompose and distribute AIML approaches using methods such as federated learning and split learning.

Intelligent Process and Factory Control

Teacher: Mathieu Moze (Cnam), Birte Glimm (UULM)

Advanced methods on control-system processes and integration of AI methods in related computations.

Wireless and Mobile Networks

Teacher: Selma Boumerdassi (Cnam), Rosario Garroppo (UNIPI)

Course on wireless network architectures, cellular networks, Wi-Fi and local wireless local area networks, personal and ad-hoc and sensor networks.

M1 – Short-Term Courses

1-week full-time courses made available on-site and/or remotely.

C and bash programming (September)

Teacher: Sami Taktak (Cnam)

This STC is meant to deliver to M1 students, not possessing sufficient basis in C programming and unix system administration, skills needed for most of the courses in computing, robotics and networking in the first year.

Sustainable IoT Architectures (June)

Teachers: Carmen Delgado (I2cat), Selma Boumerdassi (Cnam)

This Short Term Course will focus on sustainable batteryless IoT devices. In general, IoT devices run on batteries, which are short-lived, harmful to the environment and difficult to replace in hard-to-reach areas. For this reason, batteryless devices get rid of batteries by using energy harvested from the environment and storing it in a small capacitor. However, capacitors have to deal with an intermittency behaviour which results in communication and computing challenges, which will be explained in this course. We will evaluate how different technologies such as BLE or LoRaWAN deal with this new paradigm and what are the new takeaways.

Next-Generation IEEE 802.11 standards (June)

Teacher: Periklis Chatzimisios (Ihu), Pedro Braconnot Velloso (Cnam)

The purpose of this course is to bridge the gap between the well-known and widely applied IEEE 802.11 variants with the recently developed amendments, focusing on three major technical aspects/areas of interest: (i) the Physical layer (PHY) (ii) the Medium Access Control (MAC) layer and (iii) the new usage models and applications that will be supported in the coming years. The course will also discuss the fundamental characteristics of the new IEEE 802.11be standard for Wi-Fi 7, currently being developed and is expected to support real-time applications.

Data Management and Digital Transformation in Industrial Process Automation (January)

Teachers: Silvia Gonzalez (ITCL), Stefano Secci (Cnam)

The objective of this STC is to describe novel data management technologies for the integration of data in systems automation, as compared to preexisting manual processes. More precisely, the STC will cover Data Capture (connection to equipment as PLC, SCADAs, HMI, IoT Devices and integration), Data processing (using ERP, MES, CMMS, SGA, SGE management systems), Data Analytics (using AI and ML), BI decision making with AI-based models, and Maintenance of data ownership including cybersecurity and resilience aspects.

Integration of Virtual and Augmented Reality Technologies in Connected Industries (June)

Teachers: Rodrigo Varga (ITCL), Eulalie Verhulst (Cnam)

The content of the STC is to present novel hardware solutions for virtual, augmented and mixed reality, and showcase different applications of immersive technologies in industrial environments. In particular, the STC will show how digital twins intertwine with immersive technologies, explaining the advantages of immersive Human-Machine-Interfaces (HMIs) over traditional HMIs, and helping to identify situations where to apply immersive technologies to improve use cases in the industrial plant. The STC will also
present virtual simulators for education and training.

Big Data Technologies for Connected Industries (June)

Teachers: Daniele Morandi (u-Hopper), Stefano Secci (Cnam)

This STC aims at providing working knowledge on technology stacks for building big data platforms and processing pipelines for connected industries. It covers design patterns for scalable computing platforms (decoupling, asynchronicity, parallelisation), computing models (batch vs stream computing), technology enablers (e.g., message queues, relational vs non-relational databases), as well as a set of core technologies customarily used for building connected industry platforms (Kafka, Spark, Flink, Redis). We
include real-world examples and hands-on training.

Robot Predictive Maintenance (June)

Teacher: Rodrigo Varga (Itcl), Samia Bouzefrane (Cnam)

The goal of this STC is to learn how to carry out and predict maintenance tasks on Robots main constituent elements, in order to define and implement a preventive maintenance plan with a robot according to the empirical test and the manufacturer’s specifications. This includes learning the electrical-motor elements that comprise an articulated robot and understanding its operation and function, how to carry out an error diagnosis based on the robot’s operation log, and hence designing AI to prevent accidents during the maintenance of robotic equipments.

Advanced Python Programming

Teachers: Eulalie Verhulst (Cnam), Mario Patetta (Cnam)

Advanced usages of python, including for graphical processing, object-oriented programming and network traffic processing.



M1 – Semestrial Elective Courses

Complex Networks: Data Analysis and Network Science

Teachers: Camelia Chiara (UBB)

Graph theoretic operations on graph structures for representing networks and learning systems.

Networks: Complements and Applications

Teachers: Pedro Bracconot Velloso (Cnam), Michele Pagano (UNIPI)

Course on network protocols, focused on layer 3 and above, including advanced Internet architecture systems, distributed systems and networked applications such as P2P and blockchain systems.

Computer System Modeling and Verification

Teachers: Tristan Crolard (Cnam)

Course on advanced modeling of computing systems, formal methods for code and protocol verification, computer system reliability.

Parallel and Distributed System

Teachers: Stephane Rovedakis (Cnam), Marco Danelutto (UNIPI)

Peer-to-Peer Systems an Blockchain

Teachers: Stefano Secci (Cnam), Laura Ricci (UNIPI)

Datacenter Design and Operations

Teachers: Stefano Secci (Cnam), Antonio Cistemino (UNIPI)

Seminars from the Industry

Teachers: Stefano Secci (Cnam), Cristina Cervello Pastor (UPC)

Ethics and Sovereignity of Digital Infrastructures

Teachers: Stefano Secci (Cnam)



M2 – Semestrial Core Courses

Reinforcement Learning

Teachers: Stefano Secci (Cnam), Francesco De Pellegrini (AU)

Bases on reinforcement learning techniques and their application to connected systems.

Learning Robots

Teachers: Mathieu Moze (Cnam), Birte Glimm (UULM)

Application of online learning algorithms to robotics.

Robot Operating System

Teachers: Thach Ngoc Dinh (Cnam), Birte Glimm (UULM)

Design and operation of Robot Operating Systems (ROS).

Network Virtualization and Automation

Teachers: Stefano Secci (Cnam)

Advanced course on the evolutions of network switching and routing architecture toward network virtualization (NFV/MEC), softwarization (SDN) and network automation with artificial intelligence integration.

Advanced Experimental Projects

Project tutors: Stefano Secci, Sami Taktak, Stéphane Rovedakis, Pedro Braconnot Velloso (Cnam); William Diego Maza (Orange)

In this course, you will have the possibility to develop advanced projects on recent cutting-edge networking and IoT computing technologies under adoption by the industry. Technologies include software plateforms for 5G and beyond 5G systems,  edge computing, network virtualization, IoT devices and mobile applications, as well as technologies related to cybersecurity challenges, with the demonstration of novel vulnerabilities and attacks. Projects are administratively framed, tutored and evaluated as they would be run in a professional R&D environment.

M2 – Short-Term Courses

1-week full-time courses made available on-site and/or remotely.

Applied Artificial Intelligence (January)

Teachers: Daniele Morandi (u-Hopper), Stefano Secci (Cnam)

This STC aims at filling the gap between AI models and methods, as taught in academic environments, and real-world applications of AI in the connected industry sector. The STC will be organized around use cases brought forward by the organizing SMEs, and will cover forecasting, regression and classification models. The course will unveil the intricacy of working with real-world data (typically small, incomplete and ‘dirty’), and will get students familiar with practical approaches for managing efficiently the whole AI lifecycle (from data cleansing/pre-processing to training models, from deploying said models and integrating in production all the way to MLOps approaches).

WiFi and 5G Convergence in 6G (January)

Teachers: Guy Pujolle (Green Communications), Pedro Braconnot Velloso (Cnam)

This course will present the technology used in Wi-Fi networks, 5G technology will also be described in detail with its advances in the framework of O-RAN and private 5G for the industry. Then, horizontal networks will be studied using Wi-Fi direct mode and 5G D2D technique. Finally, this course will describe the convergence of 5G and Wi-Fi which will be materialized in 6G as well as the advances expected in this future generation.

Smart Industry 4.0 Systems (September)

Teachers: Guy Pujolle (Green Communications), Pedro Braconnot Velloso (Cnam)

The purpose of this course is to describe all the elements that will allow to implement the necessary processes to allow to reach the industry 4.0 paradigm. Then, we will examine and compare the various technologies capable of meeting the requirements described previously, going from field buses to 5G. We will also introduce the elements of the TSN (Time Sensitive Networking) architecture that will allow us to create a synchronous network suitable for the URLLC services demanded by industry 4.0. In the second part of the course, we will introduce artificial intelligence technologies that are implemented to reliable, control and speed up industry 4.0 processes. Several examples will be treated in the digitization and automation of factories.

Green AI Computing for Connected Industries (January)

Teacher: Guy Pujolle (Green Communications), Pedro Braconnot Velloso (Cnam)

Digital sobriety is not mere wishful thinking. In this course, we will examine all the processes of centralized or distributed artificial intelligence which can lead to minimization of the energy spent in a context of connected industries. In particular, we will focus on the more or less centralized positioning of Industry 4.0 processes, ranging from a cloud level to embedded Edge via the Fog to respond to the overall energy optimization of an industrial environment with connected companies and factories.

Communications for Precision Agriculture and Farming (September)

Teachers: Stefano Giordano (UNIPI), Samia Bouzefrane (Cnam)

This course will present the underlying communication network architectures and technologies for Precision Agriculture and Farming, one of the most important being the application level protocol that is used among IoT nodes, gateways, and application servers. We will then examine and compare the various technologies capable of meeting the requirements described previously and in particular the IoT application layer protocols, focusing on their basic characteristics, their performance as well as their recent use in agricultural applications.

Application of AI and Cyber-threat Management

Teachers: Angelo Consoli (Eclexys), Yacine Benchaib (Cnam)

Programming and Communication of a Robotic Arm

Teachers: Rodrigo Varga (ITCL), Sami Taktak (Cnam)

AI4CI Activities: from research to business

Teachers: Daniele Morandi (u-Hopper), Stefano Secci (Cnam)

FPGA Platform: Programmable Embedded System

Teachers: Jonathan Rivalan (Smile), Sami Taktak (Cnam)



M2 – Semestrial Elective Courses

Process Mining and Intelligence

Teachers: Stefano Secci (Cnam), Mario Cimino (UNIPI)

Advanced Automation of Industrial Processes and Services

Teachers: Tarek Raissi (Cnam), Birte Glimm (UULM)

Advanced Programming

Teachers: Stefano Secci (Cnam), Andrea Corradini (UNIPI)

Algorithm Engineering and Data Structures

Teachers: Stefano Secci (Cnam), Paolo Ferragina (UNIPI)

Embedded System: Cybersecurity and Applications

Teachers: Sami Taktak (Cnam)

Advanced course on the design of IoT systems and devices, related applications and cybersecurity challenges.

Français Langue Etrangère

Teachers: Elsa Chackhine (Cnam)

Optional course for those not possessing B2 level in French.

English

Teachers: Margot Salemi, Meryem Guetal (Cnam)

Optional course on professional English for those not possessing C1 level in English.


The complete course programs and additional administrative details can be found at this page. Note the master program can slightly change from one year to another one.

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