DADS 7650 — Deep Generative Methods
4 semester hours Graduate Lecture
Examines theoretical foundations of generative AI across natural language processing and computer vision. Covers deep learning architectures including autoencoders, GANs, diffusion models, and transformers. Investigates applications such as text generation, image synthesis, and retrieval-augmented generation. Reinforces concepts through a structured lab sequence that supports practical understanding and ethical considerations in AI development.
Prerequisites
Unlocks DADS 7305
Courses that list DADS 7650 in their prerequisites.
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