Understand how completion models really work, and how reinforcement learning shaped the capabilities we now use in chat and agents. Build the intuition that lets you wield LLMs intentionally — not just hope they behave.

Learn the essential techniques behind zero-shot, few-shot, and advanced prompting strategies. You'll see how to steer models reliably, even in real-world, messy tasks.

RAG is the full chain from understanding user intent, crafting smart queries, pulling the best sources, and generating grounded, high-quality outputs. You'll learn how to design each step so your applications are accurate, reliable, and aligned with what users actually need.

Build conversational agents and workflow-driven agents that stay on track and complete non-trivial tasks. Learn the design patterns that make agents useful, flexible, and powerful.

Master the techniques for offline evaluation, online observability, and iterative improvement — so you’re not flying blind as your app scales.

When prompting isn't enough, customization is key. Learn when fine-tuning is worth it – and when it's not! Land how to use lightweight LoRA techniques to teach new behaviors or specialize your models.

Stay ahead by understanding the next frontier: multimodal models, new interaction paradigms, and what’s coming next in AI development.