Advanced Machine Learning

Course Description

This graduate-level course covers advanced topics in machine learning, including deep learning architectures, reinforcement learning, generative models, and their applications to computer vision, natural language processing, and robotics.

Learning Objectives

• Master advanced deep learning architectures (CNNs, RNNs, Transformers)
• Understand and implement reinforcement learning algorithms
• Design and train generative models (GANs, VAEs, Diffusion)
• Apply ML techniques to research problems
• Read and critique ML research papers

Prerequisites

• CS401: Introduction to AI
• Strong programming skills in Python
• Graduate standing or instructor approval

Evaluation