Introduction:
The course concentrates on service architectures and also covers today’s networks, to allow the students understand the changes that the world of telecommunications and internet is facing. Message flows and procedures are thoroughly examined in class and in small student groups to strengthen understanding. The course also introduces the alternatives to operator-centric architectures to provide communication services to the users. Other approaches such as Peer-to-Peer systems, OTT, web-NGN convergence, user generated services are introduced.
Network Intelligence course encompasses four main parts. The first part of the course aims to present the background on Autonomic computing and Networking as a core stone of Network intelligence. The Second part objectives are to zoom on the algorithmic part, the possible operations (classification, clustering, etc.). The third and fourth part target to practice the of machine learning for network data (data extraction, pre-processing, model set-up, configuration and validation, etc.)
Coordinator: Noel Crespi
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Last modify 29 January 2019