Agentic AI Fundamentals: Build Real-World AI Agents

About this course

This course contains the use of artificial intelligence.

Agentic AI isn't a buzzword anymore — it's what companies are actually hiring for. This course takes you from "I understand what an LLM is" to "I can design, build, evaluate, and deploy a real autonomous AI agent" — through three complete, real-world projects, not toy examples.

What you'll build:

An Insurance Claims Assistant — a Gen AI app that extracts structured data, drafts responses, and wraps it all in a real Streamlit UI (deliberately not an agent, because you'll also learn when an agent is overkill)A Financial Research Agent — your first real autonomous agent, built with LangGraph, that reasons, plans, calls tools, and streams its thinking live to a UIAn AI Recruitment Team — a full multi-agent system with specialist agents (screening, scoring, interview questions) coordinated by a supervisor, sharing data through a real MCP server

What ties every project together:

Real APIs throughout — every exercise runs on the actual OpenAI API, not a simulationMCP (Model Context Protocol) — the emerging industry standard for connecting agents to tools, backed by Anthropic, OpenAI, and GoogleEvals that actually mean something — golden datasets, LLM-as-judge scoring, and LangSmith tracing, so you know your agent works instead of hoping it does

Guardrails against prompt injection and unsafe actions

Real deployment — packaging an agent as a FastAPI service and taking it from your laptop to a live, shareable URL

Why this course is different: Every single lecture is built around something real — a real API call, a real running app, a real evaluation run — not slides describing what "would" happen.

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