This guide goes step-by-step journey from the fundamentals of Generative AI to advanced applications. It unravels the complexities of generative models, delves into such key techniques as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders), and provides a foundation to understand the underlying principles.