Role: Main Lecturer
This course spanned 16 weeks, with 2 sessions of 1.5 hours each week. The course covered classical machine learning, representation learning, autoencoders, convolutional neural networks (CNNs), long short-term memory networks (LSTMs), generative adversarial networks (GANs), and advanced concepts like zero-shot learning and model robustness.
Role: Main Lecturer
This 16-week course included 2 sessions of 1.5 hours each week, focusing on contemporary topics in AI trustworthiness, including safety, security, fairness, bias, transparency, adversarial attacks, backdoor attacks, and membership inference attacks. The first 10 weeks were dedicated to lectures, while the remaining 6 weeks involved student presentations on selected top papers, implementation projects, and improvement under my supervision. Evaluation was based on seminars, projects, and a final exam.
Role: Main Lecturer
This course was similar to the ”Advanced Topics in AI” course at IPM, with the same structure and content. The 16-week course also included 2 sessions of 1.5 hours each week, focusing on deep learning safety and security.