Explore the foundational concepts of diffusion models in this comprehensive university lecture from UCF that delves into the first part of an introduction to these powerful machine learning tools. Learn the core principles, mathematical frameworks, and theoretical underpinnings that drive diffusion-based generative modeling, setting the stage for understanding how these models transform noise into meaningful data through a gradual denoising process. Gain valuable insights into the architecture, training methodology, and practical applications of diffusion models in modern artificial intelligence and deep learning applications during this hour-long academic presentation.