AI for Defence

Education & Training

PROGRAMME: AI for Defence (ID 6.5)

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.


  • B2 English level
  • Basic Knowledge of programming in any language

This programme is focused on:

  • Professionals working in Defence and AeroSpace Industry (up-skilling and re-skilling activities)

IMPORTANT: This prototype programme is EXCLUSIVE FOR partners of the ASSETs+ consortium and associated stakeholders.  If you want to join the ASSETs+ Stakeholders Group and become part of our ecosystem, you just have to fill out a 5 minute form here before signing up for the course.


12:30 to 13:30 (CET)
Demystifying AI

+ 5 hours of asynchronous personal work

12:30 to 13:30 (CET)
Introduction to Machine Learning
12:30 to 13:30 (CET)
The Python ecosystem for Machine Learning
12:30 to 13:30 (CET)
The Machine Learning workflow (part 1)
12:30 to 13:30 (CET)
The Machine Learning workflow (part 2)
12:30 -13:30 (CET)
Machine Learning fundamentals (part 1)
12:30 – 13:30 (CET)
Machine Learning fundamentals (part 2)
12:30 – 13:30 (CET)
Neural networks
12:30 – 13:30 (CET)
Machine Learning issues
12:30 – 13:30 (CET)
Application to malware detection

Learning outcomes:

  • Machine Learning overview
  • Machine Learning fundamentals
  • Artificial neural networks
  • Machine Learning issues
  • Prepare datasets for training
  • Build Machine Learning models on various data types
  • Use standard Python libraries for Machine Learning
  • Understand the benefits and limits of Machine Learning approaches
  • Apply Machine Learning wisely, in accordance with ethical rules

Registration closing date: 8 May, 2023