Slides

Introduction to Generative AI

Define, de-mystify, and deploy generative AI — from the history of AI to LLMs, prompting, agents, and enterprise implementation

Retrieval Augmented Generation (RAG)

Grounding language models in your own documents — embeddings, vector search, reranking, evaluation, and the decisions leaders actually own

Engineering Robust RAG Systems

From query stratification to failure mitigation — why one RAG architecture cannot serve every question, and the seven places these pipelines break

Agentic Systems

From a pattern that answers to a process that acts — the agentic loop, tools, memory, multi-agent teams, design patterns, and the autonomy decisions leaders own

RAG Evaluation

RAG Retrieval Evaluation

Responsible AI

How to govern Agentic AI systems

Starting soon...

Show message before class and during breaks