Build a strong foundation in machine learning and generative AI by exploring key algorithms, including neural networks, GANs, and transformers. Learn how large language models support chatbots and discover image and video generation techniques. Under expert guidance, you will also practice with tools like ChatGPT and Stable Diffusion.

Get introduced to generative models and understand how modern AI systems create content. Explore the architecture of large language models, learn how variational autoencoders work, and examine adversarial networks. You will also learn about attention mechanisms and transformers that power many advanced generative AI applications

Learn how to design LLM workflows using LangChain and use advanced prompt engineering techniques. Explore how to build LLM applications, work with retrieval-augmented generation, and fine-tune and customize large language models for specific use cases.

Learn the basics of agentic AI. Design LLM agents with perception layers and cognitive engines, build workflows using LangGraph, and develop multi-agent systems with AutoGen. You will also learn how to create agent teams with CrewAI and implement the Model Context Protocol for unified integration and communication across different AI systems.

Understand how denoising enables high-quality image generation. Learn the role of autoencoders in generative AI, study contrastive learning techniques, and how shared embedding spaces help models understand relationships between text, images, and other data.

Understand why governance is critical in AI and explore the challenges companies face in responsibly managing AI systems. Learn key ethical principles, governance structures, risk management strategies for AI projects, and how governance is integrated into the AI lifecycle.

Complete the Applied Generative AI course online Specialization program with a portfolio-worthy capstone project in which you will apply your newly acquired skills to work on an industry problem.