This course uses a combination of lectures and hands-on exercises to introduce students to the challenges of bias (in data and algorithms), transparency, accountability, explainability, and ethics in Artificial Intelligence (AI) and Machine Learning (ML) applications. Upon successful completion of the course, students will be able to detect biases in data, build explainable AI/ML applications, evaluate applications for fairness, and address ethical concerns associated with the deployment of AI systems. Prerequisite: INSY 5339.