Due to the COVID-19 crisis, the information below is subject to change,
in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
5 credits
30.0 h + 15.0 h
Q2
Teacher(s)
Sadre Ramin;
Language
English
Main themes
- Cellular networks
- Internet of things and sensor networks
- Mobile and embedded applications
Aims
At the end of this learning unit, the student is able to : | |
1 |
Given the learning outcomes of the "Master in Computer Science and Engineering" program, this course contributes to the development, acquisition and evaluation of the following learning outcomes:
|
Content
- Wireless sensor networks
- Internet of Things
- Programming embedded systems with network connection
- Network protocols for resource-constrained devices
- Introduction to mobile networks
Teaching methods
Due to the COVID-19 crisis, the information in this section is particularly likely to change.
The course consists of a series of lectures and accompagning exercises and project(s). The teaching method can change depending on the circumstances and the number of participating students or for other reasons. Face-to-face classes as well as remote teaching or a mix of the two methods are possible.
Evaluation methods
Due to the COVID-19 crisis, the information in this section is particularly likely to change.
Envisaged mode of evaluation:- Project (40% of the final mark)
- Exam (60% of the final mark)
Other information
Background:
- LSINF1252
- LINGI1341 (or a similar basic networking course)
Faculty or entity
INFO
Force majeure
Evaluation methods
Depending on the public health conditions during the exam period, the evaluation can take different forms:
- Group project (40% of the final mark) during the quadrimester and a written (face-to-face) exam during the exam session (60% of the final mark)
- Group project (40% of the final mark) during the quadrimester and individual projet during the exam session (60% of the final mark)
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Computer Science and Engineering
Master [120] in Computer Science
Master [120] in Electrical Engineering
Master [120] in Data Science Engineering
Master [120] in Data Science: Information Technology