Generative AI Models and Architecture
Generative AI Models and Architecture
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 45m | 113 MB
Instructor: Amber Israelsen
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 45m | 113 MB
Instructor: Amber Israelsen
AI tools are evolving fast, and understanding how they work is more important than ever. This course will teach you how generative AI models are built, how they generate content, and how to evaluate and apply them confidently in your work.
What you'll learn
Many people use generative AI tools without understanding how they work or how to assess their outputs. In this course, Generative AI Models and Architecture, you’ll learn to confidently explain, evaluate, and apply core generative AI technologies.
First, you’ll explore how transformer-based models like GPT process language using tokenization, embeddings, and attention. Next, you’ll discover how other generative architectures like GANs, VAEs, and diffusion models compare — and what they’re each designed to do. Finally, you’ll learn how to evaluate generative outputs, understand model training workflows, and recognize risks like bias and misuse.
When you’re finished with this course, you’ll have the skills and knowledge of AI model architecture needed to make smarter, more informed decisions in your work.
Generative AI Models and Architecture
