This course aims to provide computer engineering graduate students with a basic knowledge of signal processing and explainable artificial intelligence. Students will explore the design and application of explainable artificial intelligence algorithms by learning the basic properties and processing methods of signals. The course aims to develop practical application skills as well as theoretical foundations.

This course aims to teach the principles of signal processing and explainable artificial intelligence techniques to computer engineering graduate students. The course will cover the basic properties, analysis and processing of signals, and then examine the use of explainable artificial intelligence techniques. Students will understand key concepts in signal processing and explainable AI, reinforce these concepts with hands-on projects and examples, and develop skills to solve real-world problems using advanced signal processing and explainable AI technique