Introduction to Machine Learning for Electronic Warfare | On-Demand Course

Course Details

Introduction to Machine Learning for Electronic Warfare | On-Demand Course

Course Length: 21 hours total - delivered across seven sessions of 3-hours each.

Continuing Education Units (CEUs): 21

Description: This course introduces students to the fundamentals of machine learning and its application to modern Electronic Warfare (EW) and cyber solutions. Commencing with an overview of machine learning, and its recent evolution into deep learning, the course focuses on providing an education in how these algorithms work and training on how to apply them in an EW context. As an example, machine learning using neural networks will be discussed, followed by a demonstration on how to implement one to solve a classification problem using Electronic Intelligence (ELINT).

The course contains the following major topics: introduction to machine learning, classification using neural networks, training machine learning systems for EW, and developing solutions using machine learning for EW. Each topic will include lectures, demonstrations, and, for the more ambitious, an exercise to further explore the capabilities of machine learning in EW and cyber applications.

Who Should Attend: The intended audience of this course are Electronic Warfare (EW) professionals looking to expand their knowledge of the field and machine learning. No prior experience in EW is required, but a background in engineering or science is recommended.


Course Agenda

  • Session 1
    • Introduction to Machine Learning and EW
  • Session 2
    • Probability and Statistics
  • Session 3
    • Machine Learning Concepts
  • Session 4
    • Software for Machine Learning
  • Session 5
    • Applying Machine Learning
  • Session 6
    • Machine Learning and ELINT
  • Session 7
    • Machine Learning in Operation


Course Pricing

AOC Members - $420

Non-Members - $630

Want to save on your course registration? AOC Members receive discounts on all courses, free access to all webinars and much more.

NOTE: Each registration is for one (1) participant ONLY. Distributing your login information or allowing others to participate in this course with you or under your account is grounds for removal from the course without a refund of any kind.


Kyle Davidson is a former signals officer, having served for 15 years in the Canadian Army. During this time, he held a variety of positions in the field force, on operations in Afghanistan, and as an educator. For the last five years in the Army he served at the Royal Military College of Canada (RMC) as an assistant professor in the Department of Electrical and Computer Engineering, from which he holds a B.Eng. and M.A.Sc. He continues to serve as an adjunct professor at RMC and is scheduled to defend his Ph.D. in EW systems engineering in the spring of 2019.

Since leaving the Canadian Armed Forces he has worked as a Radar and Electronic Warfare Scientist and later Head of Capability at Tactical Technologies Inc., a subsidiary of Leonardo MW, on a variety of projects, often related to the Eurofighter Typhoon's defensive aid suite. He is currently the Chief Engineer for Electronic Warfare Systems at MDA where he focus ses on developing EW technologies and teams to support a variety of projects in the land, air, sea, and space domains.