EE260B: Trustworthy AI for 

Autonomous Systems

Winter 2024

Course Overview

This course aims to provide you with a comprehensive understanding of the principles and practices that underpin the development of safe and reliable AI for autonomous system applications. The course objectives include exploring the foundational and advanced concepts of trustworthy artificial intelligence and machine learning, with a particular focus on their applications in autonomous systems such as autonomous vehicles, drones, and robotic systems. Students will learn to assess and ensure the safety, reliability, and ethical implications of AI algorithms in these contexts. The course will also delve into the latest research and methodologies for creating AI systems that are safe, robust, generalizable, and explainable, emphasizing the importance of trust and ethical considerations in AI deployment. 

Through a combination of theoretical knowledge and practical case studies, you will be equipped to design, analyze, and implement AI solutions that are not only technically sound but also socially responsible and trustworthy. There will be a final course project for students to obtain hands-on research experience in related areas.

Topics Covered

Course Details

Lectures

Office Hours

Prerequisites


Grading Policy

References

There is no required textbook for this course. An in-depth understanding of the lecture slides and the set of selected papers will be sufficient for you to succeed in this course. Note there is no existing textbook that covers such a collection of topics and materials covered in this course.

Additional Recommended References: