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Agentic AI course

Agentic AI training: build systems that plan, act, and learn.

Learn the architecture behind reliable AI agents: tools, memory, planning, orchestration, MCP, evaluation, guardrails, and multi-agent systems built for production.

Quick answer

What is this page about?

Learn the architecture behind reliable AI agents: tools, memory, planning, orchestration, MCP, evaluation, guardrails, and multi-agent systems built for production. The pathway is intended for developers, product builders, and technical professionals and emphasizes practical application over passive theory.

What you will learn

From understanding to application.

01

Understand the difference between chatbots, workflows, and autonomous agents

02

Connect agents to tools, APIs, data, and secure actions

03

Design memory and context strategies for useful long-running tasks

04

Build planning, orchestration, evaluation, and guardrail loops

05

Prototype multi-agent systems with MCP and production architecture

The curriculum

A focused, useful sequence.

Learn the right concepts in the right order, then put them to work on a portfolio-ready project.

01

Agent fundamentals, task loops, and autonomy

Live instruction, guided practice, and feedback.

02

Tools, function calling, APIs, and action safety

Live instruction, guided practice, and feedback.

03

Memory, context engineering, and state

Live instruction, guided practice, and feedback.

04

Planning, orchestration, and workflow design

Live instruction, guided practice, and feedback.

05

MCP, evaluation, observability, and guardrails

Live instruction, guided practice, and feedback.

06

Capstone: build and test a production-minded AI agent

Live instruction, guided practice, and feedback.

Frequently asked

Start with clarity.

Agentic AI training: build systems that plan, act, and learn. focuses on practical skills, current AI workflows, responsible use, and outcomes learners can explain and apply.

VG

Meet your mentor

Vijay Gurunathan

Founder & Chief Architect

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17+ years of industry experienceAI engineering researcher & practitionerEnterprise and cloud architectureFormer HCL, Verizon, Ford, Daimler, Zensar, Fractal.ai

Find your path

Which AI course is right for you?

Answer four quick questions and get a practical recommendation, learning roadmap, and next step.

Where are you starting?

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Make your next move

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