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

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.