Details
This course provides a practical introduction to building and training AI models using Python and the open-source frameworks PyTorch and Ray. Participants will explore the transformative impact of Generative AI tools like ChatGPT, Gemini, and DALL-E, gaining insights into their underlying technologies.
The curriculum covers core concepts of advanced AI architectures, including Generative Adversarial Networks (GANs), Transformers, Large Language Models (LLMs), variational autoencoders, and diffusion models. Through a hands-on approach, students will develop a deep understanding of these technologies, enabling them to apply generative AI techniques to real-world applications. By the end of the course, learners will be equipped with the knowledge and practical skills needed to leverage state-of-the-art AI tools and frameworks.
What you will learn in this course
Build and train AI models with PyTorch and Ray.
Understand the principles of Generative Adversarial Networks (GANs).
Explore Transformers and their role in AI models.
Learn the fundamentals of Large Language Models (LLMs).
Develop variational autoencoders for generative tasks.
Study diffusion models and their applications.
Gain hands-on experience with state-of-the-art Generative AI tools.
Prerequisites
- AI-101 - Modern AI Python Programming
- AI-461 - Distributed AI Computing