Generative AI Fundamentals

About this course

This specialization is intended for learners with foundational knowledge in Python and Machine Learning who seek to develop a deep, hands-on understanding of Generative AI and its real-world applications. Across three courses, you’ll explore the full spectrum of GenAI. from understanding what it is and how it works, to building and deploying advanced systems responsibly. You’ll begin with the foundations of Large Language Models, learning about tokenization, embeddings, and the Transformer architecture that powers modern AI tools. Then, you’ll dive into multimodal generation, discovering how models like VAEs, GANs, Transformers, and Diffusion networks create and manipulate audio, image, and video content. In the final course, you’ll move from theory to implementation: building a Transformer from scratch in Python, extending its capabilities with Retrieval-Augmented Generation (RAG), and developing agentic AI systems using Google’s Agent Development Kit (ADK) on GCP. Throughout, you’ll engage with ethical considerations around bias, transparency, copyright, and responsible deployment.

Course objectives

• to provide a deep, practical understanding of Generative AI
• to enable students to develop agentic AI systems
• to familiarize learners with modern AI architectures and their applications