Available courses

[SecCom] Secure communications (ÖNEN, Melek)
Melek Onen

[SecCom] Secure communications (ÖNEN, Melek)

This course provides a broad introduction to cryptography and communication security mechanisms based on cryptography. The course covers fundamental aspects such as security evaluation criteria and the mathematical constructs underlying cryptographic primitives as well as applied aspects like the design of major encryption and hashing algorithms, details of security mechanisms relying on cryptography such as data encryption, integrity, digital signature, authentication,  key management, and public-key infrastructures.

Teaching and Learning Methods : Lectures and Lab sessions

Course Policies : Attendance to Lab sessions is mandatory.

[BigSec] Security and privacy for Big Data and Cloud (ÖNEN, Melek)
Melek Onen

[BigSec] Security and privacy for Big Data and Cloud (ÖNEN, Melek)

The goal of this course is to equip students with security and privacy technologies for the Big Data and the cloud computing paradigm. Students will discover the latest advances in privacy and security technologies and will understand their limitations as well.

Teaching and Learning Methods : Lectures (sometimes invited) and homeworks

Course Policies : homeworks and final project are mandatory

[ImCod] Image & Video Compression (DUGELAY, Jean-luc)
Jean-Luc Dugelay

[ImCod] Image & Video Compression (DUGELAY, Jean-luc)


Because multimedia data (in particular image and video) require efficient compression techniques in order to be stored and delivered, image and video compression is a crucial element of an effective communication system.


This course covers the most popular lossless and lossy formats, introduces the key techniques used in source coding, as well as appropriate objective/subjective metrics for visual quality evaluation.

Teaching and Learning Methods: Each class includes a problem session for students to practice the material learned. This course includes a limited number of lab session hours.

Course Policies: It is mandatory to attend lab. sessions.


[DigiCom] Digital communications (KNOPP, Raymond)
Raymond Knopp

[DigiCom] Digital communications (KNOPP, Raymond)

Digital communications is the study of physical layer transmission and reception strategies in communications equipment such as mobile communication devices, high-speed ethernet, optical communications and subscriber-line communications. It comprises the areas of (i) statistical modelling of communication channels (ii) design of coding and modulation systems for error resiliency (iii) design of demodulation and decoding strategies and the associated methods for assessing their performance. In addition to providing an overview of communication channels and classical modulation strategies, this course takes a hands-on approach by focusing on the details of a few critical elements of digital communications pertaining to modern wireless transceivers, both coherent and non-coherent.

Teaching and Learning Methods :: Lectures and hands-on lab sessions in MATLAB using signals acquired from local 4G networks.

Course Policies : Attendance to lab sessions is mandatory.

[DBSys] Database Management System Implementation (PAPOTTI, Paolo)
Paolo Papotti

[DBSys] Database Management System Implementation (PAPOTTI, Paolo)

This course covers the implementation of database systems by addressing the main topics, including data storage, indexing, querying; query optimization and execution; concurrency control and transaction management.

The purpose of the course is to become familiar with the principles and the ideas behind established techniques for handling data at scale. Students will implement classic and cutting-edge database systems methods in three projects. Projects represent the biggest chunk of this course. The projects require extending the functionality of a data management system in order to support novel features. In at least one the projects, students will also write a technical report that describes and experimentally evaluates the built system.

The course is complemented by lab sessions to guide students through the design and validation of the methods developed duringthe lectures.

Teaching and Learning Methods: Lectures and Lab sessions (preferably one student per group).

Course Policies : 

Students are expected to do their own assigned work. If it is determined that a student has engaged in any form of academic dishonesty, he or she may fail the course and additional sanctions according to Eurecom's policies.

[CompArch] Computer architecture (PACALET, Renaud)
Renaud Pacalet

[CompArch] Computer architecture (PACALET, Renaud)

This course presents the architecture of microprocessor-based systems, from the internals of the processors themselves to the main peripherals that surround them and make a complete computing machine, capable of running operating systems like GNU/Linux, Android, Windows, iOS...

Teaching and Learning Methods : Lectures, team-work, lab sessions, mini-conferences by industrials 

Course Policies : Attendance to the lab sessions and the mini-conferences is mandatory

[Clouds] Distributed Systems and Cloud Computing (APPUSWAMY, Raja)
Raja Appuswamy

[Clouds] Distributed Systems and Cloud Computing (APPUSWAMY, Raja)

The goal of this course is to provide a comprehensive view on recent topics and trends in distributed systems and cloud computing. We will discuss the software techniques employed to construct and program reliable, highly-scalable systems. We will also cover architecture design of modern datacenters and virtualization techniques that constitute a central topic of the cloud computing paradigm. The course is complemented by a number of lab sessions to get hands-on experience with Hadoop and the design of scalable algorithms with MapReduce.

Teaching and Learning Methods: Lectures and Lab sessions (group of 2 students) 

Course Policies: Attendance to Lab session is mandatory.

[WiSec] Wireless Security (FRANCILLON, Aurélien)

[WiSec] Wireless Security (FRANCILLON, Aurélien)

Wireless communications are pervasive and have been used for a century. They are used in a very large set of  security applications (communications by security forces, car key remote, alarm system, access control, drone command and control, surveillance devices) . However, day to day applications also require to be protected for privacy and personal security, such as WiFi or mobile communications (2G/3G/4G). At the same a number of challenges are present in wireless communications security, for example, messages are broadcasted, making it possible to intercept them without being noticed. Wireless signals are subject to jamming, making them unavailable.

This course will give a large perspective of the fundamental challenges in securing wireless communications, from the physical layer, modulations to the application protocols. A special focus will be put on practice with hands on exercises (using software defined radios and WiFi dongles).

Teaching and Learning Methods : Course is composed of lectures, Labs and small projects with final presentation.

Course Policies : Class attendance, labs and projects mandatory.

[WebInt] Interaction Design and Development of Modern Web Applications (TRONCY, Raphaël)
Raphael Troncy

[WebInt] Interaction Design and Development of Modern Web Applications (TRONCY, Raphaël)

Human-computer interaction (HCI) is the study of interaction between people (users) and computers, as the intersection of computer science, behavioral sciences, design and several other fields of study. This course aims to provide the basic concepts of user centered design when developing web applications. It will offer a deep dive presentation of modern web technologies: HTML5, CSS3 and Javascript. Finally, this course will provide techniques for evaluating user interfaces.

Teaching and Learning Methods:Lectures and Lab sessions (group of 2-3 students)

Course Policies: Attendance to Lab session is mandatory.

[UMLEmb] Designing embedded systems with UML (APVRILLE, Ludovic)
Ludovic Apvrille

[UMLEmb] Designing embedded systems with UML (APVRILLE, Ludovic)

« Those who fail to plan, plan to fail... ».  Architects, tailors, and directors all use plans (or models) for their creation, and software engineers are no exception. Thus, it is a common practice for software project managers to rely on the UML langage to document their software projects, and to perform modeling of the software itself. 

Teaching and Learning Methods : Lectures (20%), Exercises (40%), Lab sessions (40%) 

Course Policies: Attendance to  labs is mandatory



 

[SysSec] System and Network Security (FRANCILLON, Aurélien)
Aurelien Francillon

[SysSec] System and Network Security (FRANCILLON, Aurélien)

This course provides an introduction to practical security concepts. The goal is to understand common attacks and countermeasures in a range of topics. The course is practice oriented, it describes real attacks and countermeasures. Students will practice attacks on a dedicated server (similar to a Capture the Flag competition).

Teaching and Learning Methods :Weekly class. Some guest lectures. Homework are online challenges, on a number of topics related to the class. A first lab is organized during lecture time to bootstrap challenges.

Course Policies :Class attendance is not checked but generally required to succeed.

[STATS] Foundations of Statistical Inference (KANAGAWA, Motonobu)
Motonobu Kanagawa

[STATS] Foundations of Statistical Inference (KANAGAWA, Motonobu)

Statistics is a foundation of many areas of science and engineering that involve `` data.’’ This course focuses on fundamental concepts in statistical inference that are necessary for applying statistical methods in practice and that form the basis of other fields such as machine learning.

Teaching and Learning Methods:  Students learn by lectures, exercises, and computer experiments.

Course Policies:  The valid usage of statistical methods requires a mathematical understanding of the underlying mechanism. As such, the course covers both mathematical and algorithmic aspects of statistics.  

[Stand] Standardization activities (HÄRRI, Jérôme)
Jerome Haerri

[Stand] Standardization activities (HÄRRI, Jérôme)

(Course for Post Master and International Masters students only).

This module provides a global and coherent view of C-ITS standardization activities in major standard development organizations (SDOs) or industry consortia, such as the IEEE, the ETSI, the ISO, the IETF and the SAE. This module also illustrates the similarities and differences between different approaches in Europe, the US, and the rest of the world. This module finally details the standardization process related to different C-ITS technologies or information.

Teaching and Learning Methods : Lectures, Case Studies and attendance to Standardization meetings

Course Policies : Attendance to case studies and standardization meetings is mandatory.

 

 

[SSP] Statistical signal processing (SLOCK, Dirk)
Dirk Slock

[SSP] Statistical signal processing (SLOCK, Dirk)

The proper treatment of modern communication systems requires the modelling of signals as random processes. Often the signal description will involve a number of parameters such as carrier frequency, timing, channel impulse response, noise variance, interference spectrum. The values of these parameters are unknown and need to be estimated for the receiver to be able to proceed.

Parameters may also occur in the description of other random analysis of communication networks, or in the descriptions of sounds and images, or other data, e.g. geolocation. This course provides an introduction to the basic techniques for estimation of a finite set of parameters, of a signal spectrum or of one complete signal on the basis of a correlated signal (optimal filtering, Wiener and Kalman filtering). The techniques introduced in this course have a proven track record of many decades. They are complementary to the techniques introduced in the EURECOM course Stat. They are useful for other application branches such as machine learning, in the EURECOM courses MALIS and ASI.

Teaching and Learning Methods: Lectures, Homework, Exercise and  Lab session (groups of 1-2 students depending on size of class).

Course Policies:  Attendance of Lab session is mandatory (15% of final grade).

[SoftDev] Software development methodologies (BALZAROTTI, Davide)
Davide Balzarotti

[SoftDev] Software development methodologies (BALZAROTTI, Davide)

 This course covers a variety of topics, all related to the use and   management of a Linux operating system. In particular, the course   is divided in three parts dedicated respectively to the command-line,  to the Python programming language, and to maintaining, compiling, and  installing applications.

Teaching and Learning Methods : Lectures and Homework Assignments

[OS] Operating systems (APVRILLE, Ludovic)
Ludovic Apvrille

[OS] Operating systems (APVRILLE, Ludovic)

Would you like to investigate beyond the surface of Windows, MacOS, Linux, Android? Fed up with not understanding the origin of segmentation faults, why you need to eject a USB key before physically removing it, or why/how your Android system can execute Pokemon Go and Facebook at the same time? You want to delve into the details of the inner workings of the Linux kernel? Join us to discover the power of Operating Systems!

Teaching and Learning Methods : Lectures (40%), Lab sessions (40%), Project (20%)

Course Policies: Attendance to some lab and project session is mandatory

[Optim] Optimization Theory with Applications (SPYROPOULOS, Thrasyvoulos)
Thrasyvoulos Spyropoulos

[Optim] Optimization Theory with Applications (SPYROPOULOS, Thrasyvoulos)

Optimization theory (convex, non-convex, discrete) is an important field that has application to almost every technical and non-technical field, including wireless communication, networking, machine learning, security, transportation systems, finance (portfolio management) and operation research (supply chain, inventory). It has recently attracted even more interest, as the underlying tool for advanced machine learning techniques for big data (deep neural networks, stochastic gradient descent). In this course we will cover both the fundamentals (algorithms, duality, convergence, optimality) as well as a range of applications in the area of (network) resource allocation, distributed optimization, and machine learning. Special emphasis will be devoted to exemplify applications of optimization techniques to modern engineering and CS problems with the objective of  developing skills and background necessary to recognize, formulate, and solve optimization problems.

Teaching and Learning Methods : Lectures supported by exercise sessions, and homework assignments including both problem solving and programming of learned methods (CVX, matlab, python)

Course Policies : Attendance to lectures and exercise session is not mandatory but highly recommended.

[NetMod] Network Modeling (SPYROPOULOS, Thrasyvoulos)
Thrasyvoulos Spyropoulos

[NetMod] Network Modeling (SPYROPOULOS, Thrasyvoulos)

The goal of this course is to teach student how to model, analyze, and optimize the performance of different Networks using simple theoretical tools. The end goal is to highlight the common underlying properties, develop a strong high-level insight on the network parameters affecting network performance, and understand how to optimize a networked system. 

Each class will be a mix of some necessary theoretical tools, and their application to real-world networks. We will consider examples from modern cellular networks (e.g., offloading and load balancing), capacity planning, MAC protocols, scheduling in computing clouds and web server farms, security (e.g. virus infections), measuring large social networks like Facebook and Twitter, search engines (e.g. Google's PageRank algorithm), and many others. 

Teaching and Learning Methods :Lectures, Homework, and Programming Labs (2)

[MobSys] Mobile communication systems (NIKAEIN, Navid)
Raymond KnoppAdlen KsentiniNavid Nikaein

[MobSys] Mobile communication systems (NIKAEIN, Navid)

This course presents a series of mobile systems in their entirety to synthetize the knowledge gained in more fundamental courses. It explores current and emerging standards and follows the evolution of various mobile services.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory.

[MobServ] Mobile application and services (NIKAEIN, Navid)
Navid Nikaein

[MobServ] Mobile application and services (NIKAEIN, Navid)

This course presents the three main mobile platforms and their ecosystems, namely Android, iOS, and PhoneGap/WebOS. It explores emerging technologies and tools used to design and implement feature-rich mobile applications for smartphones and tablets taking into account both the technical constraints relative to storage capacity, processing capacity, display screen, communication interfaces, and the user interface, context and profile. 

 Teaching and Learning Methods : Lectures, Lab sessions (group of 2 students), and a challenge project ( group of up 2 4 students). 

 Course Policies : Attendance to Lab session is mandatory.


 

[MobMod] Mobility Modeling (HÄRRI, Jérôme)
Jerome Haerri

[MobMod] Mobility Modeling (HÄRRI, Jérôme)

(Course for Post Master and International Master students only).

The module teaches the state-of-the art of the modeling techniques for vehicular mobility. The objectives are first to describe the challenges of close-to-reality random models for vehicular mobility, then to introduce the concepts of vehicular traffic flow models and Origin-Destination (O-D) Matrices for trip and path planning. Finally, it trains on best practices to apply these concepts for realistic vehicular traffic modeling on vehicular traffic simulators.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory.

[MobiSec] Mobile Systems and Smartphone Security (ANTONIOLI, Daniele)
Daniele Antonioli

[MobiSec] Mobile Systems and Smartphone Security (ANTONIOLI, Daniele)


This course will discuss all relevant aspects related to mobile systems security. Mobile devices have been revolutionized users' lives, and more than two billions mobile devices have been sold to date. Unfortunately, these devices, their operating systems, and the applications running on them are affected by security and privacy concerns. This course will be hands-on and will cover topics such as the mobile ecosystem, the design and architecture of mobile operating systems, rooting and jailbreaking, application analysis, malware reverse engineering, malware detection, vulnerability assessment, automatic static and dynamic analysis, and exploitation and mitigation techniques. While this course will mostly focus on Google's Android OS (its open nature makes it possible to have more interesting exercises and projects), it will also cover technical details about Apple's iOS as well.

Teaching and Learning Methods : Lectures , labs, and homework assignments.

Course Policies : Class and lab attendance is not checked but generally required to succeed.


[MobCom] Mobile communication techniques (ELIA, Petros)
Petros Elia

[MobCom] Mobile communication techniques (ELIA, Petros)

The goal of MOBCOM is to provide a fundamental understanding of mobile communication systems. The course will seek to describe the key aspects of channel characteristics/modeling, of communication techniques, and to describe the application of these techniques in wireless communication systems.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2-3 students)

Course Policies : Attendance to Lab session is mandatory.

[MathEng] Essential Mathematical Methods for Engineers (EVANS, Nicholas)
Nicholas Evans

[MathEng] Essential Mathematical Methods for Engineers (EVANS, Nicholas)

This course aims to present a treatment of mathematical methods suitable for engineering students who are interested in the rapidly advancing areas of signal analysis, processing, filtering and estimation. Significant current applications relate to, e.g., speech and audio, music, wired and wireless communications, instrumentation, multimedia, radar, sonar, control, biomedicine, transport and navigation.  The course presents a study of linear algebra,  probability, random variables, and analogue systems as a pre-requisite to material relating to sampled-data systems.  Time permitting, the final part of the course covers the concepts of random processes, the analysis of random signals, correlation and spectral density.

Teaching and Learning Methods: The course is comprised of lectures, exercises and laboratory sessions.

Course policies: This course is aimed at students who have NOT already completed preparatory classes.  Completion of all in-lecture examples is strongly advised.

[MALIS] Machine Learning and Intelligent System (ZULUAGA, Maria A.)
Maria Zuluaga

[MALIS] Machine Learning and Intelligent System (ZULUAGA, Maria A.)

The objective of this course is to give students a solid background in Machine Learning (ML) techniques. ML techniques are used to build efficient models for problems for which an optimal solution is unknown. This course will introduce the basic theories of Machine Learning, together with the most common families of classifiers and predictors. It will identify the basic ideas underlying the mechanism of learning, and will specify the practical problems that are encountered when applying these techniques, optimization, overfitting, validation, together with possible solutions to manage those difficulties.

Teaching and Learning Methods : Lectures and Lab sessions (groups of 1 or 2 students)

Course Policies : Attendance to Lab sessions is mandatory

[InfoTheo] Information theory (GESBERT, David)
David Gesbert

[InfoTheo] Information theory (GESBERT, David)

  • Since 1948, the year of publication of Shannon's landmark paper "A mathematical theory of communications", Information theory has paved the ground for the most important developments of today's information/communication world making it perhaps the most important theoretical tool to understand the fundamentals of information technologies.
  • Information theory studies the ultimate theoretical limits of source coding and data compression, of channel coding and reliable communications via channels, and provides the guidelines for the development of practical signal-processing and coding algorithms.
  • This course covers Information theory at an introductory level.
  • The practical implications of theoretical results presented are put in evidence through examples.
  • Various perspectives are given to understand every single theoretical results from a intuitive point of view, regardless of your background or study track.

Teaching and Learning Methods : Lectures, Exercise and  Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory (25% of final grade).

[ImProc] Digital Image Processing (DUGELAY, Jean-luc)
Jean-Luc Dugelay

[ImProc] Digital Image Processing (DUGELAY, Jean-luc)


The course aims at providing students with a basic knowledge and practice about the use of computer algorithms to perform image processing on digital images. The two main objectives attached to Digital Image Processing (DIP) are to improve the visual quality of images and to automatically extract semantic information from visual data (e.g. object recognition). 

Teaching and Learning Methods: Each session is split into two parts: 1.5-hour lecture and 1.5-hour lab.

 Course Policies:  It is mandatory to attend lab. sessions.


[ATWireless] Advanced topics in wireless communications (GESBERT, David)
David Gesbert

[ATWireless] Advanced topics in wireless communications (GESBERT, David)

Hot Topics in Mobile Communications

·         This course presents some recent or emerging  HOT TOPICS within the area of mobile networks.

·         The course is modified from 2014 (and earlier) versions to allow focus on updated set of hot topics and trends in mobile communications.

·         We emphasize emerging techniques to be used in future 5G mobile networks to allow for a significant increase in user quality, and network capacity.

·         The course earns 5 ECTS

·         We cover hot topics for 5G such as "Massive MIMO" , "network cooperation", "interference management", and "device coordination". These topics cover 21 hours.

·         In the other 21hours, external experts (Intel, Huawei, ETSI, etc.) from Industry reveal hot topics seen from the wireless networking  industry.

Teaching and Learning Methods : Lectures, Exercise and  Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory (25% of final grade).

[QUANTIS] Quantum Information Science (KOUNTOURIS, Marios)
Marios Kountouris

[QUANTIS] Quantum Information Science (KOUNTOURIS, Marios)

Interested in learning how to communicate using quantum bits? Curious about how quantum algorithms and quantum computers work? This is an introductory course to quantum communication, computation, and information processing. We will cover various aspects of quantum information science and systems, introducing in a simple manner key principles and concepts, which are often considered “hard” or mysterious.

After a brief overview of quantum technology, the course starts with a concise introduction of key principles of quantum mechanics. Then, we cover fundamental aspects of quantum information, such as qubit, entanglement, Bell inequalities, and EPR (Einstein-Podolsky-Rosen) paradox, as well as of quantum communication (noise, quantum channels, decoherence, von Neumann entropy, Holevo capacity). We also present basic principles of quantum computing and study key quantum algorithms (e.g., Shor’s, Grover’s, quantum Fourier transform). Finally, we discuss potential applications and emerging topics, such as quantum AI and quantum/ post-quantum security.

Previous exposure to quantum mechanics is not required. All necessary concepts and mathematical formalism are taught during the first lectures.

Teaching and Learning Methods: Lectures supported by illustrative examples and exercises. Each session starts summarizing key concepts from previous lecture. Optional project for in-depth study of theoretical concepts or for understanding practical aspects (e.g. implementing/programming basic quantum algorithms and gates).

Course Policies: Attendance to lectures is not mandatory but highly recommended.

[MPC] Multiparty Computation and Blockchains (FAONIO, Antonio)
Antonio Faonio

[MPC] Multiparty Computation and Blockchains (FAONIO, Antonio)

The goal of this course is to introduce the students to the basic concepts of secure multiparty computation, the foundational MPC protocols and more advanced blockchains protocols.

Teaching and Learning Methods:

Lectures and homework.

Course Policies:

Final project and homework are mandatory

[EmSim] Emulation and simulation methodologies (HÄRRI, Jérôme)
Jerome Haerri

[EmSim] Emulation and simulation methodologies (HÄRRI, Jérôme)

(Course for Post Master and International Masters students only).

This module teaches the fundamentals of simulation and emulation methodologies providing guidance on how to design a performance evaluation campaign, set up a test scenario, select the appropriate models, level of granularity, metrics for statistical correctness, and discuss the differences between simulation and emulation platforms and how to use them for accurate performance evaluation of communications for ITS.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies :  Attendance to Lab session is mandatory.

[AwaRe] Awareness-raising to research
Jean-Luc Dugelay

[AwaRe] Awareness-raising to research


The objective of this course is to familiarize Master students with the research community, both from academia and industry.


Several speakers from different background will explain their motivation to have chosen to do a Ph.D. and will share their personal experience since then accumulated during their career. The course will include several Q&A sessions, the selection and reading of a scientific article co-authored by a young researcher.The objective of this course is to familiarize Master students with the research community, both from academia and industry.


Several speakers from different background will explain their motivation to have chosen to do a Ph.D. and will share their personal experience since then accumulated during their career. The course will include several Q&A sessions, the selection and reading of a scientific article co-authored by a young researcher.


[ManagIntro] Introduction to management (POPE, Kenneth)
Ken Pope

[ManagIntro] Introduction to management (POPE, Kenneth)

This course is like a mini-MBA (Masters' in Business Administration) and covers much of the same ground as a business school classical post-experience MBA (though not in the same depth). This is one of a triad of related courses all of which are of special interest to those intending to become managers (practically everyone!), or, eventually, owners of their own companies.

Teaching and Learning Methods: Lectures, team exercises, and presentations

Course Policies: On-time class attendance is mandatory; three unapproved absences mean exclusion.

 

[TeamLead] Personal Development and Team Leadership (POPE, Kenneth)
Ken Pope

[TeamLead] Personal Development and Team Leadership (POPE, Kenneth)

This course consists of three essential elements:

(1)     'Know yourself' - understanding the drivers of your own behavior. This is the basis of any personal development and is critical for developing effective interaction with others whether as a team member, or as a team leader.

(2)    'Working with others' - building on the self-knowledge mentioned above, this core element allows you to explore, understand, and practice ways of working with others that are both more enjoyable and more effective. This is critical given that almost everyone works as part of a team.

(3)    'What's next?' - building on both the above sections, this element helps you take the next steps in your career: setting objectives, selecting target organizations, applying for jobs, and effective interviewing.

Teaching and Learning Methods: Lectures, team exercises, and presentations

Course Policies: On-time class attendance is mandatory; three unapproved absences mean exclusion.

[RDI] Responsible Digital Innovation: Risks, Ethics and Technology (DRAETTA, Laura)
Laura Draetta

[RDI] Responsible Digital Innovation: Risks, Ethics and Technology (DRAETTA, Laura)

This course is an introduction to responsible innovation (RI), notably in the digital domain. It provides conceptual and empirical bases for students to approach technology and innovation by focusing on the issues they raise in terms of ethics and risks for human health and the environment. These issues will be addressed from a sociological perspective based on a multilevel analysis of stakeholders' action. Students will learn the key concepts of the RI field (eg sustainability, acceptability, anticipation, participation) as well as some technology assessment methods, that will be useful to better understand the contemporary challenges and controversies of the digital era. The seven sessions of the course will be structured around a permanent dialogue between researchers and practitioners of innovation. They will will cover a range of case studies including human exposure to EMF, smart meters for energy transition, e-waste and digital identity.

Teaching and Learning Methods: The course is organized as a workshop where the sessions will be held by social scientists and innovation practitioners from outside the academic field (industry, consulting). It is based on a participative pedagogy, requiring the active involvement of students, both in class (discussions, presentations, tutorials, MCQ) and at home (readings, web research, writing). A collective research work of knowledge formalization will be required throughout the course and presented at the end of the course.

Course Policies: On-time class attendance is mandatory and will be recorded at each session. Each not excused absence will reduce the final grade by three points. If you are more than 15 minutes late, you will be counted absent. After three absences, even if excused, you will have to pass a final exam. 

[CSE] The challenges of a sustainable economy (SAFA, Alain)

[CSE] The challenges of a sustainable economy (SAFA, Alain)

Thiscourse aims to start with the circular flow of economic activity and the interdependence of its institutional sectors. The evolution of sustainable development’s concept is developed with its economic, social and environmental dimensions. It highlights the challenges and commitments to be met at national and international level. Corporate social responsibility towards the various stakeholders is an essential step in the achievement of a sustainable economy.

Teaching and Learning Methods

A course of 5 sessions around the fundamentals of the concept of sustainable development.

Students will then have to apply their knowledge in 2 sessions through:

  • Presentation (student subgroups) on a topical subject related to sustainable economy challenges.
  • Debriefing and discussion

Course Policies: Seven 3-hour sessions.

[I&E] Innovation and entrepreneurship EIT (external course) (HERLIN, Séverine)
Severine Herlin

[I&E] Innovation and entrepreneurship EIT (external course) (HERLIN, Séverine)

Course for EIT students only

Two topics – with related concepts, methods and/or tools – will be covered in the context of a selected innovation or entrepreneurial case:

 

•             One fixed and common topic: Assessing the impact of a technology on an industry, market and/or organization, the support and barriers to its deployment, the influence on a specific goal/agenda (technology transfer, existing industry, new company, etc.).

•             One case-dependent topic: pertaining to market / business environment analysis (main forces affecting the business, suppliers, partners, competition, environmental issues), sustainability and social issues, business modeling, go-to-market strategies, etc.

 

The innovation or entrepreneurial project may be originating from:

•             Cases issued from EIT Digital Innovation Action Lines: within Activities, Partners / Business Community projects,

•             Cases based on the continuation of students EIT Digital Summer School (or BDLab) project,

•             Cases within other innovation or entrepreneurial projects rooted in a real-life environment as may be collected in the university ecosystem.

 

Teaching and Learning Methods :

 

The I&E Study is based on a group assignment and on an individual assignment. A large autonomy is given to the students to organize and achieve their goals.

a. Group assignment:

Students will work in teams of around 4 students. Teams will be assigned cases. Each team will identify and address a challenge/question in the context of their assigned case. This challenge/question may be related to considering alternate business models or go-to-market scenarios in relation with the innovation or entrepreneurial case, fed by exploration in some specific areas: business environment, competition, suppliers, partners, environmental and sustainability issues, etc.

To address their challenge/question, the students will cover the 4 generic steps of an explorative business analysis:

  • Identification of the relevant challenge/question,
  • Acquisition of applicable concepts/methods/tools,
  • Observations (data collection) on a selected part of the case,
  • Analysis and interpretation.

 

Students’ supervision comprises:

  • One individual or group session to introduce and detail the assignment and help students identify the challenges/questions,
  • 1-to-many workshops: one for each of the 4 study steps above. Students support can be structured through pre-/post-assignments for each workshop,
  • One oral defense.

 

It is expected that the authors of the case will contribute to supervision, provide data/contacts, participate to an oral defense and/or offer other meeting occasions to ensure rooting of the business assignment in real life.

b. Individual assignment:

Students will work on an online individual assignment. This individual assignment can be done before, during or after the group assignment. In this assignment, students will acquire concepts and tools pertaining to the assessment of the impact of a technology on an industry, market and/or organization. Students will also get the opportunity to apply these concepts and tools to their own case (based on their group-assignment case when possible).

Students’ supervision comprises (may be combined with the group assignment supervision):

  • One group session to introduce and detail the assignment,
  • 1-to-many workshops to help students follow the steps in the assignment structure.

 

 

Cour

[B_INNOV] How to adopt the right posture and move from idea to market! (HERLIN, Séverine)
Severine HerlinPatrick Sure

[B_INNOV] How to adopt the right posture and move from idea to market! (HERLIN, Séverine)

Thanks to this class, you will understand why an innovative project cannot be considered as a regular project.You will learn how to take the market into account at a very early stage in project management, how to link technology and needs and how to lead in a time of uncertainty and complexity. You will be trained to build a solid and convincing launching strategy as a team on specific cases that you choose. Whatever the nature or maturity of a project, you will learn to identify its potential and market, to choose the most relevant positioning and to build a viable business model.

You have an innovative idea that you would like to expand in the market. You want to know if you are made for entrepreneurship. You plan to work in a R&D company or in an innovation department. Or you are simply curious to know how to innovate better. This course is for you!

Teaching and learning methods:

The pedagogy of this course is deliberately interactive through the application of new concepts studied on concrete cases. We will use the pedagogical tools developed by Vianeo (card game, paper canvas, digital platform) and the participants' cases throughout the course in teams of 5 or 6.

Course Policies: Mandatory attendance. Between 2 courses, work on collecting information, further analysis, updating or preparation.

[Property] Intellectual property law (SERIO, Dominique)

[Property] Intellectual property law (SERIO, Dominique)

This course provides a solid introduction to intellectual property law from a managerial and strategic perspective taking an international and comparative approach.

The course is the study of how companies protect innovations   in order to create value for the company

Teaching and Learning Methods : Lectures and cases  sessions (group of 4 students)

Course Policies : Attendance to Lab session is mandatory.

[WebSem] Semantic Web and Information Extraction technologies (TRONCY, Raphaël)
Raphael Troncy

[WebSem] Semantic Web and Information Extraction technologies (TRONCY, Raphaël)

The Semantic Web is an evolving extension of the World Wide Web in which the semantics of information and services on the web is defined. It derives from W3C director Sir Tim Berners-Lee's vision of the Web as a universal medium for data, information, and knowledge exchange. This course is a guided tour for a number of W3C recommendations allowing to represent (RDF/S, SKOS, OWL) and query (SPARQL) knowledge on the web as well as the underlying logical formalisms of these languages, their syntax and semantics. We will present the problems of modeling ontologies and reconciling data on the web. Finally, we will explain how to extract knowledge from textual documents using natural language processing and information extraction technologies.

Teaching and Learning Methods:Lectures and Lab sessions (group of 2 students max)

Course Policies:Attendance to Lab session is mandatory.

[TraffEEc] Emission and Traffic  Efficiency (HÄRRI, Jérôme)
Jerome Haerri

[TraffEEc] Emission and Traffic Efficiency (HÄRRI, Jérôme)

(Course for Post Master ITS  and International Master students only).

 

This module addresses mechanisms and strategies to improve traffic efficiency and carbon footprint. The objectives are first to introduce the underlying theory such as Waldrop Equilibrium required for efficient path planning. Second, it describes concepts and theory behind the optimization of traffic lights to traffic conditions. Third, it provides guidelines and methodologies to model emissions and integrate them into efficient path planning.  Finally, it trains on best practices to apply these concepts for efficient and green path planning on vehicular traffic simulators.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory

[Speech] Speech and audio processing (EVANS, Nicholas)
Nicholas Evans

[Speech] Speech and audio processing (EVANS, Nicholas)

This course provides an introduction to the automatic processing of speech and audio signals.  It starts with a treatment of the human speech production and perception mechanisms and looks at how our understanding of them has influenced attempts to process speech and audio signals automatically.  The course then considers the analysis, coding and parameterisation of signals in the case of different speech and audio processing tasks.  After an introduction to essential pattern recognition techniques, the course considers specific applications including speech recognition, speaker recognition and speaker diarization.  The course also includes a treatment of speech and audio coding, noise compensation and speech enhancement.

Teaching and Learning Methods:

The course is comprised of lectures and exercises and laboratory sessions.

Course policies: Attendance of laboratory sessions is mandatory.

[SP4COM] Signal Processing for Communications (SLOCK, Dirk)
Dirk Slock

[SP4COM] Signal Processing for Communications (SLOCK, Dirk)

The subtitle of this course could be “Multi-Antenna Interference Handling for Multi-User Multi-Cell Systems”. Indeed the main focus is on the exploitation of multiple antennas to (more easily) handle inter-symbol and inter-user interference. Key concepts here are beamforming, MIMO (Multi-Input Multi-Output), Multi-User MIMO, Massive MIMO.

After a basic course in digital communications, a wide range of issues arise in the treatment of physical layer procedures in a wide variety of transmission technologies such as xDSL, gigabit Ethernet, powerline systems, DAB/DVB broadcasting and optical communication systems to name a few. These issues involve e.g. multi-rate echo cancellation for full duplex operation on twisted pair telephone lines, synchronization and equalization techniques in a variety of single and multi-carrier systems, impulsive noise in powerline and automotive systems etc. Even just wireless communications encompass a wide range of systems such as satellite, underwater, near-field communications, fixed wireless access, private systems, sensors, IoT, etc. and a wide range of aspects such as relaying, full duplex radio, cognitive radio, location estimation etc.

Whereas these systems will be briefly mentioned, the main focus will be on cellular wireless and the use of multiple antennas at receivers and transmitters. Spatial filtering, spatiotemporal filtering, and multiuser detection for CDMA are all treated in a unified fashion.

Teaching and Learning Methods: Lectures, Exercise and  Lab session (groups of 1-2 students depending on size of class).

Course Policies: Attendance of Lab session is mandatory (25% of final grade).

[Radio] Radio engineering (KALTENBERGER, Florian)
Florian Kaltenberger

[Radio] Radio engineering (KALTENBERGER, Florian)

This course treats the subject of modern radio engineering and includes typical RF architectures and their characterizations, modeling, prediction and simulation of radio-wave propagation, cellular planning, systems-level aspects of modern radio network design.

 Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

 Course Policies : Attendance to Lab session is mandatory.

[ProtIOT] Iot Communication Protocols (KSENTINI, Adlen)
Adlen Ksentini

[ProtIOT] Iot Communication Protocols (KSENTINI, Adlen)

This course covers the Low Power Wide Area Network (LPWAN) protocols dedicated to IOT. LPWAN is a technology that intends to offer Internet connectivity to a large number of objects   ("Things") under very strict requirements in terms of cost, power consumption, long distance, battery life, indoor penetration, etc. This course presents two families of LPWA protocols specially developed for IOT: (i) LPWAN for unlicensed spectrum (e.g. LoRa, SigFox ...) and (ii) Cellular LPWAN for licensed spectrum (e.g. 3GPP LTE Cat. M1 or Cat. NB).

Teaching and Learning Methods: The course is organized in 4 lectures and 3 labs.

Course Policies: Labs are Mandatory (attendance + reports)

[PlanTP] Transportation Planning (HÄRRI, Jérôme)
Jerome Haerri

[PlanTP] Transportation Planning (HÄRRI, Jérôme)

(Course for Post Master  et  international Master students only).This module addresses mechanisms and strategies to model multi-modal transportation. The objectives are first to introduce concepts of population modeling. Second, it extends graph theory concepts for modeling heterogeneous transportation networks, in particular public transport networks. Mechanisms for activity and demand modeling for multimodal transportation will also be discussed. Finally, this lecture trains on best practices to apply these concepts for efficient multimodal transportation planning on vehicular traffic simulator

 

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies :  Attendance to Lab session is mandatory.

[NetSoft] Network Softwerization (KSENTINI, Adlen)
Adlen Ksentini

[NetSoft] Network Softwerization (KSENTINI, Adlen)

The architectures of networks and service delivery platforms are subject to an unprecedented techno-economic transformation. This trend, often referred to as Network Softwarization, will yield significant benefits in terms of reducing expenditure and operational costs of next generation networks. The key enablers are Network Function Virtualization (NFV), Software-Defined Networking (SDN), Cloud Computing (mainly Edge Computing).

This course will cover the principle of Network Softwerization by introducing and detailing the concepts of SDN, NFV and Cloud Computing (focusing on the IaaS model and Edge Computing). Besides covering the theoretical aspects, the course will provide an overview of the enabling technologies, and how combining these concepts will allow building flexible and dynamic virtual networks tailored to services, e.g. Anything as a Service (AaaS) and Network Slicing. 

Teaching and Learning methods:

-          Be able to control a network using a NoS (SDN controller)

-          Be able to deploy a virtual network architecture

[Net_Sec] Network Security: practical hands on approach" (DACIER, Marc)

[Net_Sec] Network Security: practical hands on approach" (DACIER, Marc)

This course presents the main applications of secure communication mechanisms in the area of computer networks and distributed systems. The course covers network security approaches based on firewalls, cryptographic security protocol suites designed for the data exchange and network control components of Internet, wireless security protocols, and security solutions for mobile network architectures.

Teaching and Learning Methods : Lectures and Lab sessions

Course Policies : Attendance to Lab sessions is mandatory.

[MobWat] Wireless Access Technologies (HÄRRI, Jérôme)
Jerome Haerri

[MobWat] Wireless Access Technologies (HÄRRI, Jérôme)

This module addresses the access methods in Wireless Local Access Networks (WLAN). The basic contention and management mechanisms are detailed. Current and emerging standards of WLAN toward 5G are also presented.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies :  Attendance to Lab session is mandatory.

[MobAdv] Mobile Advanced Networks (NIKAEIN, Navid)
Navid Nikaein

[MobAdv] Mobile Advanced Networks (NIKAEIN, Navid)

Teaching and Learning Methods: Lectures, Homework (2-3), and a case study (study and present a research paper in a group of 2-3 students). 

Course Policies: Mandatory participation, Case study optional, but recommended.

[MALCOM] Machine Learning for Communication Systems (KOUNTOURIS, Marios)
Marios Kountouris

[MALCOM] Machine Learning for Communication Systems (KOUNTOURIS, Marios)


This course introduces fundamental concepts in machine learning (ML), with particular emphasis on communication-efficient distributed learning and applications to networked systems. After a brief introduction to ML methods and deep neural networks (adapted to enrolled students’ prior knowledge), we present key aspects for their efficient application to communication systems. We will cover applications that span different layers and system configurations, including physical layer (signaling, detection), multiple access and radio resource management. We then focus on large-scale distributed and decentralized learning in wireless networks, in particular under constraints (completion time, radio resources, computational efficiency, etc.). We also cover reinforcement learning and theoretical ML topics (generalization, approximation, fairness). Finally, we highlight key challenges in realizing the promise of machine learning for communication networks.

Teaching and Learning Methods: Lectures, exercise sessions, lab sessions, and potentially homework assignments including both problem solving and programming of learned methods. Each session starts summarizing key concepts from previous lecture. Part of each lecture is dedicated to illustrative examples and exercises.

Course Policies: Attendance to lab session is mandatory. Attendance to lectures and exercise sessions is highly recommended.


[ImSecu] Imaging Security (DUGELAY, Jean-luc)
Jean-Luc Dugelay

[ImSecu] Imaging Security (DUGELAY, Jean-luc)


Image & Video processing is part of many applications related to security: digital watermarking, steganography, image forensics, biometrics, and video surveillance.

  • Digital Watermarking allows owners or providers to hide an invisible and robust message inside a digital Multimedia document, mainly for security purposes such as owner or content authentication. There is a complex trade-off between the different parameters : capacity, visibility and robustness.
  • Steganographyis the art and science of writing hidden messages (in a picture or a video) in such a way that no-one apart from the sender and intended recipient even realizes there is a hidden message.
  • Image Forensics includes two main objectives: (1) To determine through which data acquisition device a given image is generated; (2) To determine whether a given image has undergone any form of modification or processing.
  • Biometrics: The security fields uses three different types of authentication : something you know, something you have, ore something you are : a biometric. Common physical biometrics includes fingerprints, hand geometry ; and retina, iris or facial characteristics. Behavioural characters include signature, voice. Ultimately, the technologies could find their strongest role as intertwined and complementary pieces of a multifactor authentication system. In the future biometrics is seen playing a key role in enhancing security, residing in smart cards and supporting personalized Web e-commerce services. Personalization through person authentication is also very appealing in the consumer product area. This course will focus on enabling technologies for Biometrics, with a particular emphasis on person verification and authentication based on or widely using image/video processing.
  • Video surveillance is the monitoring of the behavior, activities, or other changing information, usually of people for the purpose of influencing, managing, directing, or protecting. By default, for a better scene understanding, automatic image processing tools are used between acquisition/transmission and visualization or storage

Teaching and Learning Methods: Ce cours comporte un nombre limité de Travaux Pratiques et Travaux Dirigés.


 

Course Policies: Les TPs sont obligatoires.


[FormalMet] FormalMethods-Formal specification and verification of systems (AMEUR, Rabea)
Rabea Ameur

[FormalMet] FormalMethods-Formal specification and verification of systems (AMEUR, Rabea)

The aims of the course are to provide students with tools that can help to design error-free software/hardware systems. The course  gives both the theoretical foundations and the pratical use of formal methods.

Teaching and Learning Methods : Lectures and Lab sessions.

Course Policies : Attendance to Lab session is mandatory.

[Forensics] Cyber-crime and Computer Forensics (BALZAROTTI, Davide)
Davide Balzarotti

[Forensics] Cyber-crime and Computer Forensics (BALZAROTTI, Davide)

 

The course is roughly divided in two separate parts. The first covers the   topics of computer forensics and incident response. In particular, we   discuss a number of techniques and open source tools to acquire and   analyze network traces, hard disk images, Windows and Linux operating   system artifacts, log files, and memory images.

The second part of the course deals with the analysis of malware and   unknown binaries. Here the goal is to introduce students to the main  classes of techniques used in malware analysis and reverse engineering.   We cover both static techniques (ELF and PE file structures,   dissasseblers and decompilers, data and control flow analysis, abstract   interpretation, ...) and dynamic techniques (sandboxing, library and   syscall traces, dynamic instrumentation, debugging, taint analysis,   unpacking,...). We will use mostly open source tools, with the exception of IDA Pro.

Teaching and Learning Methods :  Lectures and Homework Assignment

[DigitalSystems] Digital systems, hardware - software integration (PACALET, Renaud)
Renaud Pacalet

[DigitalSystems] Digital systems, hardware - software integration (PACALET, Renaud)

This course provides an overview of software and hardware design for smart objects. It shows how to specify, design and validate digital hardware components, how to integrate them in a microprocessor-based system, and how to drive them from the software layers.

Teaching and Learning Methods: Lectures, team-work, lab sessions. Students are provided with prototyping boards and design tools for the whole semester duration.

Course Policies: Attendance to the lab sessions is mandatory

[DeepLearning] Deep Learning (MICHIARDI, Pietro)
Pietro Michiardi

[DeepLearning] Deep Learning (MICHIARDI, Pietro)


Deep Learning is a new approach in Machine Learning which allows to build models that have shown superior performance fora wide range of applications, in particular Computer Vision and Natural Language Processing. Thanks to the joint availability of large data corpus and affordable processing power, Deep Learning has revived the old field  of Artificial Neural Networks and provoked the "Renaissance" of AI (Artificial Intelligence). The objective of this course is to provide an overview of the field of Deep Learning, starting from simple Neural Network architectures and pursuing with contemporary and state of the art practices and models. The course is organized as a combination of  lectures where the theory is exposed and discussed, and hands-on sessions (labs) where experimentations are performed to practice with the theoretical concepts.

Teaching and Learning Methods : The course is composed of a combination of lectures and labs.

Course Policies : Attendance to all sessions is mandatory.


[CompMeth] Computational Methods for digital communications (KNOPP, Raymond)
Raymond Knopp

[CompMeth] Computational Methods for digital communications (KNOPP, Raymond)

Computational methods in digital communications provides a selection of hands-on experiments in programming and implementation techniques for high-performance computing applied to telecommunications. Students will learn architecture concepts and how to optimize software to implement different types of algorithms efficiently on software-based systems.

Teaching methods: The course is primarily given in a lab setting leveraging guided personal work. The instructor gives some lecture material progressively during the course of the lab-sessions in an on-demand fashion. The mini-project teamwork includes regular 45 minutes review meetings with the instructor and teaching assistants to overview progress on the subject.

Grading: 50% final mini-project work and presentation, 50% grading of lab sessions.

[ASI] Advanced Statistical Inference
Maurizio Filippone

[ASI] Advanced Statistical Inference


This course focuses on the principles of learning from data and quantification of uncertainty, by complementing and enriching the Introduction to Statistical Learning course. In particular, the course is divided into two main parts that correspond to the supervised and unsupervised learning paradigms. The presentation of the material follows a common thread based on the probabilistic data modeling approach, so that many classical algorithms, such as least squares and k-means, can be seen as special cases of inference problems for more general probabilistic models. Taking a probabilistic view also allows the course to derive inference algorithms for a class of nonparametric models that have close connections with neural networks and support vector machines. Similarly to the Introduction to Statistical Learning course, the focus is not on the algorithmic background of the methods, but rather on their mathematical and statistical foundations. This advanced course is complemented by lab sessions to guide students through the design and validation of the methods developed duringthe lectures.

Teaching and Learning Methods : Lectures and Lab sessions (preferably one student per group)

Course Policies : Attendance of Lab sessions is mandatory


[APPIOT] Iot Application Protocols (KSENTINI, Adlen)
Adlen Ksentini

[APPIOT] Iot Application Protocols (KSENTINI, Adlen)

This course covers the application-level protocols dedicated to IOT. Knowing the limited capacity, in terms of battery and CPU, of the things, the classical application protocols used in the Internet like HTTP are not adequate. This course presents the recent application protocols specially developed for IOT. These protocols are organized into two categories: (i) Client/server (like COAP) and (ii) Publish/Subscribe (like MQTT, XMPP). In addition to these protocols, this course introduces two types of architecture, specifically dedicated to host IOT services, like 3GPP MTC and oneM2M.

Teaching and Learning Methods: The course is organised in lectures and labs.

Course Policies: Labs are Mandatory (attendance + reports)

[AML] Algorithmic Machine Learning (MICHIARDI, Pietro)
Pietro Michiardi

[AML] Algorithmic Machine Learning (MICHIARDI, Pietro)

The goal of this course is to offer data science projects to students to gain hands-on experience with several aspects of machine learning in the wild. It nicely merges the theoretical concepts students can learn in our courses on machine learning and statistical inference, and systems concepts we teach in systems courses.

The prerequisites for this course are: MALIS and Deep Learning. Optionally, familiarity with the concepts developed in the ASI course can be useful too. Students who never took any course in machine learning may experience an overload, due to both the necessity to master theoretical aspects and computer science aspects of the field.

This course is organized around Jupyter notebooks. Notebooks require to address several challenges, that can be roughly classified in:

* Data preparation and cleaning
* Building descriptive statistics of the data
* Working on a selected algorithm, e.g., for building a statistical model
* Working on experimental validation

Students are expected to work throughout the semester on their projects, in groups. As this is a very practical course, there is no frontal lecture.

[3DGraph] 3-D and virtual imaging (analysis and synthesis) (GROS, Pascal)
Pascal Gros

[3DGraph] 3-D and virtual imaging (analysis and synthesis) (GROS, Pascal)

This course introduces the main concepts and techniques used in computer graphics and image synthesis. It focuses on 3D object modelling and advanced visualization methods used in 3D and Virtual imaging, scientific and information visualization, CAD, flight simulation, games, advertising and movie special effects. The courses mixes theoretical and practical sessions and the project requires a student personal involvement.

Teaching and Learning Methods  :Lectures, Lab sessions and project  (groups of 2 to 4 students)

Course Policies : It is mandatory to

  • Attend to all the Lab sessions
  • Deliver of a project movie and attend the project contest.

[HWSec] Hardware Security (PACALET, Renaud)
Renaud Pacalet

[HWSec] Hardware Security (PACALET, Renaud)

This course offers a survey of several well-known attacks targeting specific weaknesses of hardware (microprocessors, dedicated hardware cryptographic accelerators...) For each of them the conditions of success are explained and some countermeasures are proposed.

Teaching and Learning Methods : Lectures, lab sessions 

[TeamLead] Personal Development and Team Leadership (POPE, Kenneth)
Ken Pope

[TeamLead] Personal Development and Team Leadership (POPE, Kenneth)


This course consists of three essential elements:


(1)     'Know yourself' - understanding the drivers of your own behavior. This is the basis of any personal development and is critical for developing effective interaction with others whether as a team member, or as a team leader.


(2)    'Working with others' - building on the self-knowledge mentioned above, this core element allows you to explore, understand, and practice ways of working with others that are both more enjoyable and more effective. This is critical given that almost everyone works as part of a team.


(3)    'What's next?' - building on both the above sections, this element helps you take the next steps in your career: setting objectives, selecting target organizations, applying for jobs, and effective interviewing.

Teaching and Learning Methods: Lectures, team exercises, and presentations

Course Policies: On-time class attendance is mandatory; three unapproved absences mean exclusion.


[SATT] Sociological Approaches of Telecom Technologies (RELIEU, Marc)
Marc Relieu

[SATT] Sociological Approaches of Telecom Technologies (RELIEU, Marc)

Contemporary works in the sociology of Technology offer numerous critics of the classical divide between technical and social features. It has been shown that the success or failure of technical innovations rests on their propensity to merge with various organizational and interactional features. This course aims at providing students with a precise understanding of different combinations between technologies and conversational features. Various case studies of  technologies in use will be examined, either in professional or ordinary or in mundane contexts.  Drawing from those studies, the course provide several methodological  discussions, with a strong focus on observation of social conduct in natural settings and the use of audio or video recordings in social science.

Teaching and Learning Methods : Lectures , written and oral presentations and discussions, readings

Course Policies : On-time attendance is mandatory

[ProjMan] Project management (AUREGLIA, Jean Jacques)
Jean-Jacques Aureglia

[ProjMan] Project management (AUREGLIA, Jean Jacques)

The project oriented approach is considered in leading companies as an efficient method to manage both market and client oriented deliverables (i.e. products and services) as well as investments. In order to better manage and control projects, enterprises often evolve from a “Functional organisation” into a “Matrix organisation”, in which a new breed of leaders appears: Project Managers. The Project Management Profession becomes a key element in the new and global enterprise model.
The EURECOM Global Project Management class aims at introducing the different Project Management concepts and techniques, mixing “main tent” presentation of key topics and hands-on case studies for each student to experience team dynamics and managing sample projects.

Teaching and Learning Methods include Lectures (all attendees) and Case Study sessions (in groups).
A case study in the technology domain will be performed during the course, from session to session. The main purpose of this case study is to illustrate, use and get familiar with the different Project Management methods and techniques introduced during the lectures. The case study may require some work between the class sessions. Students will present their work to the whole class for the purpose of sharing and obtaining feed-back. In order to optimize the effectiveness of each session, the students will be expected to keep the topics addressed in earlier sessions fresh in their mind, prepare for the case study, and actively participate through questions and presentation of the results of the case study.

Course Policies: Attendance is Mandatory for Both Lectures and Case Study sessions.
Non-attendance would need to be justified by serious reasons and limited to a maximum of 2.  
Active participation in the Case Study sessions is expected.

[Business] Business Simulation (POPE, Kenneth)
Ken Pope

[Business] Business Simulation (POPE, Kenneth)


In the Business Simulation course, students, in groups of four to six, will manage a virtual company as an aid to learning, by doing, about the practical aspects of running a company in a dynamic international environment. The course will be provided in a compact blended learning environment.

Teaching and Learning Methods:


Uniquely at Eurecom, this course will be delivered in a blended learning environment. That is, only half of the learning will take place in the classroom at fixed times each week. The other half of the course will be undertaken online at times, and places, suitable for the individual student teams, provided that the required tasks (usually a decision set) is completed within the defined week timeframe.


Research has shown that the best learning experience from the business simulation is over a concentrated timeframe. Therefore, this course, of the standard 42 hours effective learning time for a 5-credit program, will be completed over seven weeks elapsed time (rather than the standard 14 weeks). Some students may find this helpful; freeing up time towards the end of the semester to work on projects in other courses.


During the course, following initial briefings, student teams will each take up to 12 sets of business decisions; each decision set representing one quarter of a business year. Decisions are entered online before a predefined cutoff date and time. These decision sets drive the simulation, the results being provided online. During the seven classroom sessions, instructors will be available, face-to-face, to answer questions and provide support. Between the classroom sessions, instructors are available online (asynchronously, and, at pre-agreed times, live), as are a range of online support materials, including videos and guides.


Teaching will combine classroom and video-based instruction, guidance, and support, with additional online materials and individual support helping students, at their own time and pace, to master the technical and practical aspects of the simulation.

Course Policies


Active participation is required from each student. The grading system is continuous (see below) and is on both team and individual results. On-time attendance at entire classroom sessions is mandatory and will be recorded. Unapproved absences may result in expulsion. Individual student participation during the online sessions will be monitored by the teams themselves. Peer reviews are part of the evaluation process. In the final classroom session, each team, involving each individual student, will present their results to the class and to assessors.


 


[STATS] Foundations of Statistical Inference (M.KANAGAWA)
Motonobu Kanagawa

[STATS] Foundations of Statistical Inference (M.KANAGAWA)

Statistics is a foundation of many areas of science and engineering that involve `` data.’’ This course focuses on fundamental concepts in statistical inference that are necessary for applying statistical methods in practice and that form the basis of other fields such as machine learning.

Teaching and Learning Methods:  Students learn by lectures, exercises, and computer experiments.

Course Policies:  The valid usage of statistical methods requires a mathematical understanding of the underlying mechanism. As such, the course covers both mathematical and algorithmic aspects of statistics.  

[ATWireless] Advanced topics in wireless communications (D.GESBERT)
David Gesbert

[ATWireless] Advanced topics in wireless communications (D.GESBERT)

Hot Topics in Mobile Communications

·         This course presents some recent or emerging  HOT TOPICS within the area of mobile networks.

·         The course is modified from 2014 (and earlier) versions to allow focus on updated set of hot topics and trends in mobile communications.

·         We emphasize emerging techniques to be used in future 5G mobile networks to allow for a significant increase in user quality, and network capacity.

·         The course earns 5 ECTS

·         We cover hot topics for 5G such as "Massive MIMO" , "network cooperation", "interference management", and "device coordination". These topics cover 21 hours.

·         In the other 21hours, external experts (Intel, Huawei, ETSI, etc.) from Industry reveal hot topics seen from the wireless networking  industry.

Teaching and Learning Methods : Lectures, Exercise and  Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory (25% of final grade).

[CompArch] Computer architecture (R.PACALET)
Renaud Pacalet

[CompArch] Computer architecture (R.PACALET)

This course presents the architecture of microprocessor-based systems, from the internals of the processors themselves to the main peripherals that surround them and make a complete computing machine, capable of running operating systems like GNU/Linux, Android, Windows, iOS...

Teaching and Learning Methods : Lectures, team-work, lab sessions, mini-conferences by industrials 

Course Policies : Attendance to the lab sessions and the mini-conferences is mandatory

[Stand] Standardization activities (J.HÄRRI)
Jerome Haerri

[Stand] Standardization activities (J.HÄRRI)

(Course for Post Master and International Masters students only).

This module provides a global and coherent view of C-ITS standardization activities in major standard development organizations (SDOs) or industry consortia, such as the IEEE, the ETSI, the ISO, the IETF and the SAE. This module also illustrates the similarities and differences between different approaches in Europe, the US, and the rest of the world. This module finally details the standardization process related to different C-ITS technologies or information.

Teaching and Learning Methods : Lectures, Case Studies and attendance to Standardization meetings

Course Policies : Attendance to case studies and standardization meetings is mandatory.

 

 

[DigiCom] Digital communications (R.KNOPP)
Raymond Knopp

[DigiCom] Digital communications (R.KNOPP)

Digital communications is the study of physical layer transmission and reception strategies in communications equipment such as mobile communication devices, high-speed ethernet, optical communications and subscriber-line communications. It comprises the areas of (i) statistical modelling of communication channels (ii) design of coding and modulation systems for error resiliency (iii) design of demodulation and decoding strategies and the associated methods for assessing their performance. In addition to providing an overview of communication channels and classical modulation strategies, this course takes a hands-on approach by focusing on the details of a few critical elements of digital communications pertaining to modern wireless transceivers, both coherent and non-coherent.

Teaching and Learning Methods :: Lectures and hands-on lab sessions in MATLAB using signals acquired from local 4G networks.

Course Policies : Attendance to lab sessions is mandatory.

[MobMod] Mobility Modeling (J.HÄRRI)
Jerome Haerri

[MobMod] Mobility Modeling (J.HÄRRI)

(Course for Post Master and International Master students only).

The module teaches the state-of-the art of the modeling techniques for vehicular mobility. The objectives are first to describe the challenges of close-to-reality random models for vehicular mobility, then to introduce the concepts of vehicular traffic flow models and Origin-Destination (O-D) Matrices for trip and path planning. Finally, it trains on best practices to apply these concepts for realistic vehicular traffic modeling on vehicular traffic simulators.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory.

[InfoTheo] Information theory (D.GESBERT)
David Gesbert

[InfoTheo] Information theory (D.GESBERT)

  • Since 1948, the year of publication of Shannon's landmark paper "A mathematical theory of communications", Information theory has paved the ground for the most important developments of today's information/communication world making it perhaps the most important theoretical tool to understand the fundamentals of information technologies.
  • Information theory studies the ultimate theoretical limits of source coding and data compression, of channel coding and reliable communications via channels, and provides the guidelines for the development of practical signal-processing and coding algorithms.
  • This course covers Information theory at an introductory level.
  • The practical implications of theoretical results presented are put in evidence through examples.
  • Various perspectives are given to understand every single theoretical results from a intuitive point of view, regardless of your background or study track.

Teaching and Learning Methods : Lectures, Exercise and  Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory (25% of final grade).

[MobCom] Mobile communication techniques (P.ELIA)
Petros Elia

[MobCom] Mobile communication techniques (P.ELIA)

The goal of MOBCOM is to provide a fundamental understanding of mobile communication systems. The course will seek to describe the key aspects of channel characteristics/modeling, of communication techniques, and to describe the application of these techniques in wireless communication systems.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2-3 students)

Course Policies : Attendance to Lab session is mandatory.

[BigSec] Security and privacy for Big Data and Cloud (M.ÖNEN)
Melek Onen

[BigSec] Security and privacy for Big Data and Cloud (M.ÖNEN)

The goal of this course is to equip students with security and privacy technologies for the Big Data and the cloud computing paradigm. Students will discover the latest advances in privacy and security technologies and will understand their limitations as well.

Teaching and Learning Methods : Lectures (sometimes invited) and homeworks

Course Policies : homeworks and final project are mandatory

[MobServ] Mobile application and services (N.NIKAEIN)
Navid Nikaein

[MobServ] Mobile application and services (N.NIKAEIN)

This course presents the three main mobile platforms and their ecosystems, namely Android, iOS, and PhoneGap/WebOS. It explores emerging technologies and tools used to design and implement feature-rich mobile applications for smartphones and tablets taking into account both the technical constraints relative to storage capacity, processing capacity, display screen, communication interfaces, and the user interface, context and profile. 

 Teaching and Learning Methods : Lectures, Lab sessions (group of 2 students), and a challenge project ( group of up 2 4 students). 

 Course Policies : Attendance to Lab session is mandatory.


 

[MobiSec] Mobile Systems and Smartphone Security (Y.FRATANTONIO)

[MobiSec] Mobile Systems and Smartphone Security (Y.FRATANTONIO)

This course will discuss all relevant aspects related to mobile systems security. Mobile devices have been revolutionized users' lives, and more than two billions mobile devices have been sold to date. Unfortunately, these devices, their operating systems, and the applications running on them are affected by security and privacy concerns. This course will be hands-on and will cover topics such as the mobile ecosystem, the design and architecture of mobile operating systems, rooting and jailbreaking, application analysis, malware reverse engineering, malware detection, vulnerability assessment, automatic static and dynamic analysis, and exploitation and mitigation techniques. While this course will mostly focus on Google's Android OS (its open nature makes it possible to have more interesting exercises and projects), it will also cover technical details about Apple's iOS as well.

Teaching and Learning Methods : Lectures , labs, and homework assignments.

Course Policies : Class and lab attendance is not checked but generally required to succeed.

[MobSys] Mobile communication systems
Raymond KnoppAdlen KsentiniNavid Nikaein

[MobSys] Mobile communication systems

This course presents a series of mobile systems in their entirety to synthetize the knowledge gained in more fundamental courses. It explores current and emerging standards and follows the evolution of various mobile services.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory.

[WiSec] Wireless Security (A.FRANCILLON)
Aurelien Francillon

[WiSec] Wireless Security (A.FRANCILLON)

Wireless communications are pervasive and have been used for a century. They are used in a very large set of  security applications (communications by security forces, car key remote, alarm system, access control, drone command and control, surveillance devices) . However, day to day applications also require to be protected for privacy and personal security, such as WiFi or mobile communications (2G/3G/4G). At the same time a number of challenges are present in wireless communications security, for example, messages are broadcasted, making it possible to intercept them without being noticed. Wireless signals are subject to jamming, making them unavailable.

This course will give a large perspective of the fundamental challenges in securing wireless communications, from the physical layer, modulations to the application protocols. A special focus will be put on practice with hands on exercises (using software defined radios and WiFi dongles).

Teaching and Learning Methods : Course is composed of lectures, Labs and small projects with final presentation.

Course Policies : Class attendance, labs and projects mandatory.

[Net_Prog] Hands on approach to computer networking (M.DACIER)

[Net_Prog] Hands on approach to computer networking (M.DACIER)

  • This course provides a broad overview of computer networking, covering the application layer, transport layer, network layer, and link layers.
  • It covers basic concepts in computer networking as well as the prominent Internet protocols.
  • It is intended for students who have had no previous course in computer networking.

Teaching and Learning Methods : Lectures, homeworks and Lab sessions

Course Policies :  homeworks, quizzes and lab sessions are graded.

[DBSys] Database Management System Implementation (P.PAPOTTI)
Paolo Papotti

[DBSys] Database Management System Implementation (P.PAPOTTI)

This course covers the implementation of database systems by addressing the main topics, including data storage, indexing, querying; query optimization and execution; concurrency control and transaction management.

The purpose of the course is to become familiar with the principles and the ideas behind established techniques for handling data at scale. Students will implement classic and cutting-edge database systems methods in three projects. Projects represent the biggest chunk of this course. The projects require extending the functionality of a data management system in order to support novel features. In at least one the projects, students will also write a technical report that describes and experimentally evaluates the built system.

The course is complemented by lab sessions to guide students through the design and validation of the methods developed duringthe lectures.

Teaching and Learning Methods: Lectures and Lab sessions (preferably one student per group).

Course Policies : 

Students are expected to do their own assigned work. If it is determined that a student has engaged in any form of academic dishonesty, he or she may fail the course and additional sanctions according to Eurecom's policies.

[OS] Operating systems (L.APVRILLE)
Ludovic Apvrille

[OS] Operating systems (L.APVRILLE)

Would you like to investigate beyond the surface of Windows, MacOS, Linux, Android? Fed up with not understanding the origin of segmentation faults, why you need to eject a USB key before physically removing it, or why/how your Android system can execute Pokemon Go and Facebook at the same time? You want to delve into the details of the inner workings of the Linux kernel? Join us to discover the power of Operating Systems!

Teaching and Learning Methods : Lectures (40%), Lab sessions (40%), Project (20%)

Course Policies: Attendance to some lab and project session is mandatory

[ImProc] Digital Image Processing (J.-L. DUGELAY)
Jean-Luc Dugelay

[ImProc] Digital Image Processing (J.-L. DUGELAY)

The course aims at providing students with a basic knowledge and practice about the use of computer algorithms to perform image processing on digital images. The two main objectives attached to Digital Image Processing (DIP) are to improve the visual quality of images and to automatically extract semantic information from visual data (e.g. object recognition). 

Teaching and Learning Methods: Each session is split into two parts: 1.5-hour lecture and 1.5-hour lab.

 Course Policies:  It is mandatory to attend lab. sessions.

[SoftDev] Software development methodologies (D.BALZAROTTI)
Davide Balzarotti

[SoftDev] Software development methodologies (D.BALZAROTTI)

 This course covers a variety of topics, all related to the use and   management of a Linux operating system. In particular, the course   is divided in three parts dedicated respectively to the command-line,  to the Python programming language, and to maintaining, compiling, and  installing applications.

Teaching and Learning Methods : Lectures and Homework Assignments

[ImCod] Image & Video Compression (J.-L. DUGELAY)
Jean-Luc Dugelay

[ImCod] Image & Video Compression (J.-L. DUGELAY)

Because multimedia data (in particular image and video) require efficient compression techniques in order to be stored and delivered, image and video compression is a crucial element of an effective communication system.

This course covers the most popular lossless and lossy formats, introduces the key techniques used in source coding, as well as appropriate objective/subjective metrics for visual quality evaluation.

Teaching and Learning Methods: Each class includes a problem session for students to practice the material learned. This course includes a limited number of lab session hours.

Course Policies: It is mandatory to attend lab. sessions.

[UMLEmb] Designing embedded systems with UML (L.APVRILLE)
Ludovic Apvrille

[UMLEmb] Designing embedded systems with UML (L.APVRILLE)

« Those who fail to plan, plan to fail... ».  Architects, tailors, and directors all use plans (or models) for their creation, and software engineers are no exception. Thus, it is a common practice for software project managers to rely on the UML langage to document their software projects, and to perform modeling of the software itself. 

Teaching and Learning Methods : Lectures (20%), Exercises (40%), Lab sessions (40%) 

Course Policies: Attendance to  labs is mandatory



 

[WebInt] Interaction Design and Development of Modern Web Applications (R.TRONCY)
Raphael Troncy

[WebInt] Interaction Design and Development of Modern Web Applications (R.TRONCY)

Human-computer interaction (HCI) is the study of interaction between people (users) and computers, as the intersection of computer science, behavioral sciences, design and several other fields of study. This course aims to provide the basic concepts of user centered design when developing web applications. It will offer a deep dive presentation of modern web technologies: HTML5, CSS3 and Javascript. Finally, this course will provide techniques for evaluating user interfaces.

Teaching and Learning Methods:Lectures and Lab sessions (group of 2-3 students)

Course Policies: Attendance to Lab session is mandatory.

[Clouds] Distributed Systems and Cloud Computing (R.APPUSWAMY)
Raja Appuswamy

[Clouds] Distributed Systems and Cloud Computing (R.APPUSWAMY)

The goal of this course is to provide a comprehensive view on recent topics and trends in distributed systems and cloud computing. We will discuss the software techniques employed to construct and program reliable, highly-scalable systems. We will also cover architecture design of modern datacenters and virtualization techniques that constitute a central topic of the cloud computing paradigm. The course is complemented by a number of lab sessions to get hands-on experience with Hadoop and the design of scalable algorithms with MapReduce.

Teaching and Learning Methods: Lectures and Lab sessions (group of 2 students) 

Course Policies: Attendance to Lab session is mandatory.

[SSP] Statistical signal processing (D.SLOCK)
Dirk Slock

[SSP] Statistical signal processing (D.SLOCK)

The proper treatment of modern communication systems requires the modelling of signals as random processes. Often the signal description will involve a number of parameters such as carrier frequency, timing, channel impulse response, noise variance, interference spectrum. The values of these parameters are unknown and need to be estimated for the receiver to be able to proceed.

Parameters may also occur in the description of other random analysis of communication networks, or in the descriptions of sounds and images, or other data, e.g. geolocation. This course provides an introduction to the basic techniques for estimation of a finite set of parameters, of a signal spectrum or of one complete signal on the basis of a correlated signal (optimal filtering, Wiener and Kalman filtering). The techniques introduced in this course have a proven track record of many decades. They are complementary to the techniques introduced in the EURECOM course Stat. They are useful for other application branches such as machine learning, in the EURECOM courses MALIS and ASI.

Teaching and Learning Methods: Lectures, Homework, Exercise and  Lab session (groups of 1-2 students depending on size of class).

Course Policies:  Attendance of Lab session is mandatory (15% of final grade).

[NetMod] Network Modeling (T.SPYROPOULOS)
Thrasyvoulos Spyropoulos

[NetMod] Network Modeling (T.SPYROPOULOS)

The goal of this course is to teach student how to model, analyze, and optimize the performance of different Networks using simple theoretical tools. The end goal is to highlight the common underlying properties, develop a strong high-level insight on the network parameters affecting network performance, and understand how to optimize a networked system. 

Each class will be a mix of some necessary theoretical tools, and their application to real-world networks. We will consider examples from modern cellular networks (e.g., offloading and load balancing), capacity planning, MAC protocols, scheduling in computing clouds and web server farms, security (e.g. virus infections), measuring large social networks like Facebook and Twitter, search engines (e.g. Google's PageRank algorithm), and many others. 

Teaching and Learning Methods :Lectures, Homework, and Programming Labs (2)

[SecCom] Secure communications (M.ÖNEN)
Melek Onen

[SecCom] Secure communications (M.ÖNEN)

This course provides a broad introduction to cryptography and communication security mechanisms based on cryptography. The course covers fundamental aspects such as security evaluation criteria and the mathematical constructs underlying cryptographic primitives as well as applied aspects like the design of major encryption and hashing algorithms, details of security mechanisms relying on cryptography such as data encryption, integrity, digital signature, authentication,  key management, and public-key infrastructures.

Teaching and Learning Methods : Lectures and Lab sessions

Course Policies : Attendance to Lab sessions is mandatory.

[SysSec] System and Network Security (A.FRANCILLON)
Aurelien Francillon

[SysSec] System and Network Security (A.FRANCILLON)

This course provides an introduction to practical security concepts. The goal is to understand common attacks and countermeasures in a range of topics. The course is practice oriented, it describes real attacks and countermeasures. Students will practice attacks on a dedicated server (similar to a Capture the Flag competition).

Teaching and Learning Methods :Weekly class. Some guest lectures. Homework are online challenges, on a number of topics related to the class. A first lab is organized during lecture time to bootstrap challenges.

Course Policies :Class attendance is not checked but generally required to succeed.

[Optim] Optimization Theory with Applications (T.SPYROPOULOS)
Thrasyvoulos Spyropoulos

[Optim] Optimization Theory with Applications (T.SPYROPOULOS)

Optimization theory (convex, non-convex, discrete) is an important field that has application to almost every technical and non-technical field, including wireless communication, networking, machine learning, security, transportation systems, finance (portfolio management) and operation research (supply chain, inventory). It has recently attracted even more interest, as the underlying tool for advanced machine learning techniques for big data (deep neural networks, stochastic gradient descent). In this course we will cover both the fundamentals (algorithms, duality, convergence, optimality) as well as a range of applications in the area of (network) resource allocation, distributed optimization, and machine learning. Special emphasis will be devoted to exemplify applications of optimization techniques to modern engineering and CS problems with the objective of  developing skills and background necessary to recognize, formulate, and solve optimization problems.

Teaching and Learning Methods : Lectures supported by exercise sessions, and homework assignments including both problem solving and programming of learned methods (CVX, matlab, python)

Course Policies : Attendance to lectures and exercise session is not mandatory but highly recommended.

[ManagIntro] Introduction to management (K.POPE)

[ManagIntro] Introduction to management (K.POPE)

This course is like a mini-MBA (Masters' in Business Administration) and covers much of the same ground as a business school classical post-experience MBA (though not in the same depth). This is one of a triad of related courses all of which are of special interest to those intending to become managers (practically everyone!), or, eventually, owners of their own companies.

Teaching and Learning Methods: Lectures, team exercises, and presentations

Course Policies: On-time class attendance is mandatory; three unapproved absences mean exclusion.

 

[I&E] Innovation and entrepreneurship EIT (external course) (S.HERLIN)
Severine Herlin

[I&E] Innovation and entrepreneurship EIT (external course) (S.HERLIN)

Course for EIT students only

Two topics – with related concepts, methods and/or tools – will be covered in the context of a selected innovation or entrepreneurial case:

 

•             One fixed and common topic: Assessing the impact of a technology on an industry, market and/or organization, the support and barriers to its deployment, the influence on a specific goal/agenda (technology transfer, existing industry, new company, etc.).

•             One case-dependent topic: pertaining to market / business environment analysis (main forces affecting the business, suppliers, partners, competition, environmental issues), sustainability and social issues, business modeling, go-to-market strategies, etc.

 

The innovation or entrepreneurial project may be originating from:

•             Cases issued from EIT Digital Innovation Action Lines: within Activities, Partners / Business Community projects,

•             Cases based on the continuation of students EIT Digital Summer School (or BDLab) project,

•             Cases within other innovation or entrepreneurial projects rooted in a real-life environment as may be collected in the university ecosystem.

 

Teaching and Learning Methods :

 

The I&E Study is based on a group assignment and on an individual assignment. A large autonomy is given to the students to organize and achieve their goals.

a. Group assignment:

Students will work in teams of around 4 students. Teams will be assigned cases. Each team will identify and address a challenge/question in the context of their assigned case. This challenge/question may be related to considering alternate business models or go-to-market scenarios in relation with the innovation or entrepreneurial case, fed by exploration in some specific areas: business environment, competition, suppliers, partners, environmental and sustainability issues, etc.

To address their challenge/question, the students will cover the 4 generic steps of an explorative business analysis:

  • Identification of the relevant challenge/question,
  • Acquisition of applicable concepts/methods/tools,
  • Observations (data collection) on a selected part of the case,
  • Analysis and interpretation.

 

Students’ supervision comprises:

  • One individual or group session to introduce and detail the assignment and help students identify the challenges/questions,
  • 1-to-many workshops: one for each of the 4 study steps above. Students support can be structured through pre-/post-assignments for each workshop,
  • One oral defense.

 

It is expected that the authors of the case will contribute to supervision, provide data/contacts, participate to an oral defense and/or offer other meeting occasions to ensure rooting of the business assignment in real life.

b. Individual assignment:

Students will work on an online individual assignment. This individual assignment can be done before, during or after the group assignment. In this assignment, students will acquire concepts and tools pertaining to the assessment of the impact of a technology on an industry, market and/or organization. Students will also get the opportunity to apply these concepts and tools to their own case (based on their group-assignment case when possible).

Students’ supervision comprises (may be combined with the group assignment supervision):

  • One group session to introduce and detail the assignment,
  • 1-to-many workshops to help students follow the steps in the assignment structure.

 

 

Cour

[TeamLead] Personal Development and Team Leadership (K.POPE)
Ken Pope

[TeamLead] Personal Development and Team Leadership (K.POPE)

This course consists of three essential elements:

(1)     'Know yourself' - understanding the drivers of your own behavior. This is the basis of any personal development and is critical for developing effective interaction with others whether as a team member, or as a team leader.

(2)    'Working with others' - building on the self-knowledge mentioned above, this core element allows you to explore, understand, and practice ways of working with others that are both more enjoyable and more effective. This is critical given that almost everyone works as part of a team.

(3)    'What's next?' - building on both the above sections, this element helps you take the next steps in your career: setting objectives, selecting target organizations, applying for jobs, and effective interviewing.

Teaching and Learning Methods: Lectures, team exercises, and presentations

Course Policies: On-time class attendance is mandatory; three unapproved absences mean exclusion.

[RDI] Responsible Digital Innovation: Risks, Ethics and Technology (L.DRAETTA)
Laura Draetta

[RDI] Responsible Digital Innovation: Risks, Ethics and Technology (L.DRAETTA)

This course is an introduction to responsible innovation (RI), notably in the digital domain. It provides conceptual and empirical bases for students to approach technology and innovation by focusing on the issues they raise in terms of ethics and risks for human health and the environment. These issues will be addressed from a sociological perspective based on a multilevel analysis of stakeholders' action. Students will learn the key concepts of the RI field (eg sustainability, acceptability, anticipation, participation) as well as some technology assessment methods, that will be useful to better understand the contemporary challenges and controversies of the digital era. The seven sessions of the course will be structured around a permanent dialogue between researchers and practitioners of innovation. They will will cover a range of case studies including human exposure to EMF, smart meters for energy transition, e-waste and digital identity.

Teaching and Learning Methods: The course is organized as a workshop where the sessions will be held by social scientists and innovation practitioners from outside the academic field (industry, consulting). It is based on a participative pedagogy, requiring the active involvement of students, both in class (discussions, presentations, tutorials, MCQ) and at home (readings, web research, writing). A collective research work of knowledge formalization will be required throughout the course and presented at the end of the course.

Course Policies: On-time class attendance is mandatory and will be recorded at each session. Each not excused absence will reduce the final grade by three points. If you are more than 15 minutes late, you will be counted absent. After three absences, even if excused, you will have to pass a final exam. 

[B_INNOV] How to adopt the right posture and move from idea to market! (S.HERLIN)
Severine Herlin

[B_INNOV] How to adopt the right posture and move from idea to market! (S.HERLIN)

Thanks to this class, you will understand why an innovative project cannot be considered as a regular project.You will learn how to take the market into account at a very early stage in project management, how to link technology and needs and how to lead in a time of uncertainty and complexity. You will be trained to build a solid and convincing launching strategy as a team on specific cases that you choose. Whatever the nature or maturity of a project, you will learn to identify its potential and market, to choose the most relevant positioning and to build a viable business model.

You have an innovative idea that you would like to expand in the market. You want to know if you are made for entrepreneurship. You plan to work in a R&D company or in an innovation department. Or you are simply curious to know how to innovate better. This course is for you!

Teaching and learning methods:

The pedagogy of this course is deliberately interactive through the application of new concepts studied on concrete cases. We will use the pedagogical tools developed by Vianeo (card game, paper canvas, digital platform) and the participants' cases throughout the course in teams of 5 or 6.

Course Policies: Mandatory attendance. Between 2 courses, work on collecting information, further analysis, updating or preparation.