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Agentic AI & AI Agents

Build autonomous agents that use tools, retrieve knowledge, and act.

4.9(980 ratings)8.1K learnersAdvancedEnglishUpdated Jun 2026

Created by Kabir Anand · Agent Systems Architect · ex-OpenAI

What you'll learn

Wire LLM tool/function calling and the agent loop (ReAct)
Give agents knowledge with RAG and durable memory
Plan and execute multi-step tasks reliably
Use agent frameworks (LangGraph / OpenAI Agents SDK)
Orchestrate multi-agent systems with guardrails + human-in-the-loop
Evaluate, cost-control, and ship agents to production

Course content

3 sections · 13 lessons · 5h 2m

  • LLM APIs & tool/function calling22m
  • What is an agent? (perceive → reason → act)20m

Requirements

  • Comfortable calling an API and reading JSON
  • Basic Python; you've used an LLM API before
  • Finished Prompt Engineering or equivalent (recommended)

Description

Go beyond chat. Build AI agents that perceive, reason, and act — calling tools, retrieving knowledge, remembering state, and planning multi-step tasks. Start with tool/function calling and the ReAct loop, move through RAG, memory, planning and agent frameworks, then reach GOD tier: multi-agent orchestration, safety guardrails, human-in-the-loop, cost control, and shipping a real agent to production.

Your instructor

KA

Kabir Anand

Agent Systems Architect · ex-OpenAI

Builds autonomous agents that use tools and act safely in production. Agents, end to end.

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