"I think the course is excellent."
— Dr. Peter Norvig, Researcher at Recursive / Education Fellow at Stanford & co-author of Artificial Intelligence: A Modern Approach
"For those looking for an insightful, comprehensive outline of Agentic AI, this course is a must."
- Dr. Anoop Sinha, Research Director, Google
Agentic AI: From Fundamentals to Production takes you from core LLM concepts to designing, building, and operating autonomous AI agents across six courses and 20 modules.
Start with LLM fundamentals, inference, and prompt engineering.
Build agents from the ground up: architectures, tool use, MCP integration, memory, and RAG.
Advance to planning, design patterns, frameworks, and multi-agent orchestration.
Build responsibly with safety, privacy, and governance guardrails.
Rigorously evaluate, benchmark, and test agent behavior before it ships.
Deploy, optimize, and operate agents at scale with AI Ops.
By the end, you'll be able to build reliable, cost-efficient agentic systems ready for real-world use.
Applied Learning Project
Across all 20 modules, learners build one continuous project: an Investment Assistant agent.
Each module's hands-on lab reinforces what was just taught. The agent starts as a simple stoc question and grows into a production system with tools, memory, RAG over SEC filings, multi-agent collaboration, human-in-the-loop approval, safety testing, evaluation gates, and monitored deployment. Because the domain stays the same, each new technique is applied directly to an authentic, evolving codebase. By solving this authentic real-world problem end to end, you learn to design, test, and operate agents that deliver reliable analysis at scale.
