Format: Online
Language: English
EQF level: 6
Dates: 22 May – 9 June, 2023
Registration closing date: 8 May, 2023
Instructor: Baptiste PESQUET
Hours: 10 + 5 hours of asynchronous personal work
Host institution: University of Bordeaux / Bordeaux INP (France)
This module is an overview of Artificial Intelligence and Machine Learning, with a focus on their application to the Defence sector.
We’ll discover the Machine Learning workflow on a real-world example. Fundamentals (data management, model training, and result assessment) will be addressed. The artificial neural networks paradigm will be studied up to Deep Learning, using state-of-the-art tools from the rich Python ecosystem.
But Artificial Intelligence is not all about technique, and issues like bias, fairness and robustness will also be presented. In order to acquire practical skills, several exercises and a hands-on application of Machine Learning to malware detection will be proposed to attendees.
Pre-requisites:
| 22/05/2023 12:30 to 13:30 (CET) |
Demystifying AI |
+ 5 hours of asynchronous personal work |
| 23/05/2023 12:30 to 13:30 (CET) |
Introduction to Machine Learning | |
| 25/05/2023 12:30 to 13:30 (CET) |
The Python ecosystem for Machine Learning | |
| 26/05/2023 12:30 to 13:30 (CET) |
The Machine Learning workflow (part 1) | |
| 30/05/2023 12:30 to 13:30 (CET) |
The Machine Learning workflow (part 2) | |
| 01/06/2023 12:30 -13:30 (CET) |
Machine Learning fundamentals (part 1) | |
| 05/06/2023 12:30 – 13:30 (CET) |
Machine Learning fundamentals (part 2) | |
| 06/06/2023 12:30 – 13:30 (CET) |
Neural networks | |
| 08/06/2023 12:30 – 13:30 (CET) |
Machine Learning issues | |
| 09/06/2023 12:30 – 13:30 (CET) |
Application to malware detection |
IMPORTANT: This programme is EXCLUSIVE FOR partners of the ASSETs+ Consortium and members of our Network. If you want to become part of our ecosystem, you just have to fill out a 2 minute form here before signing up for the course below.
Registration closing date: 8 May, 2023
The European Commission’s support for the production of this publication does not constitute an endorsement of the contents, which reflect the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.
