Course description |
This training module introduces students to Artificial Intelligence (AI) and Machine Learning (ML) and is intended for aviation professionals of all levels who would like to get a basic understanding of AI and ML while exploring some of the challenges associated with this technology and its applications in the aviation industry.
|
Prerequisites |
There are no prerequisites for this module.
|
Objectives |
At the end of the course the student will be able to:
-
Explain basic AI/ML concepts and techniques
-
Select appropriate AI/ML techniques to solve simple real-world problems
-
Describe how AI/ML are being applied to aviation
-
Identify new applications of AI/ML in aviation
-
Explain the challenges associated with AI/ML in the context of aviation
-
Examine the impact of an AI/ML system on human-machine interaction
-
Discuss the pillars of trustworthy AI
|
Program |
This course will cover the following themes:
-
Basic AI/ML concepts and terminology
-
Enablers of AI and ML
-
Capabilities of AI and ML
-
Types of ML (Supervised, Unsupervised and Reinforcement Learning)
-
Basic ML techniques and associated challenges
-
Current and emerging real-world applications of AI/ML in the aviation sector
-
Building blocks of trustworthy AI
|
Book |
S. J. Russel and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed. Prentice Hall, 2020.
“Artificial Intelligence Roadmap: A human-centric approach to AI in Aviation,” European Union Aviation Safety Agency (EASA), Version 1, Feb. 2020. Accessed on June 2, 2022. [Online]. Available: https://www.easa.europa.eu/downloads/109668/en
“The FLY AI Report: Demystifying and Accelerating AI in Aviation/ATM,” European Aviation Artificial Intelligence High Level Group (EAAI HLG), March 2020. Accessed on June 2, 2022. [Online]. Available: https://www.eurocontrol.int/publication/fly-ai-report
|
Exercises |
The assessment exercises of this course comprise: a glossary; drag-and-drop exercises; discussion forums; a concept map; a case study; and multiple choice questions. Students will also be assessed on their level of participation. Most of the assessments will be graded.
|
Professor |
Barbara Sani,
Jason Gauci
|
Video professors |
|
List of video lessons |
|
|
|
|
|
Jason Gauci
|
|
|
Jason Gauci
|
|
|
Jason Gauci
|
|
|
Jason Gauci
|
|
|
Jason Gauci
|
|
|
|
|