Generative AI Training Built for Real Careers

What is Generative AI, and why does it matter?

Generative AI refers to models that can produce new text, images, code and structured content rather than simply classifying or predicting from existing data. Since the release of large language models like GPT-4 and Claude, it has moved from research labs into everyday business tools — customer support, content drafting, code generation, and internal knowledge assistants are now common production use cases. Companies use generative AI to cut the time spent on repetitive drafting work, to build assistants that can reason over internal documents, and to prototype products faster than traditional development allows. The demand for people who can design prompts, build retrieval-augmented systems, and responsibly deploy these models in production has grown faster than almost any other skill area in technology over the past three years. Our Generative AI track focuses on practical application: how to structure prompts that produce reliable output, how to connect a model to your own data using retrieval-augmented generation, how to build simple agents that can call tools and APIs, and how to evaluate and monitor a generative system once it's live. You'll work with the same APIs and frameworks — OpenAI, Claude, LangChain, and vector databases — that production teams use today, and you'll leave with a portfolio of working projects rather than just theoretical knowledge. The future scope here is significant: as more enterprises move from experimentation to production deployment, professionals who understand both the capabilities and the failure modes of these systems will be in sustained demand.