Disclosure first, because it matters: I'm a registered member of the Microsoft Student Ambassadors program, and the links in this post carry my contributor ID — that's how the program tracks that I shared them. The modules are completely free either way, and I'd share this path even if nobody was counting, because I went looking for exactly this and most of what I found was a sales page for a paid course.

The problem with learning AI agents right now

Search "learn AI agents" and you get two things: hype threads, and courses that cost money before they teach you anything. Meanwhile the companies actually building this stuff publish their own training for free — it's just badly marketed. Microsoft Learn is the clearest example I found.

The path (3 modules, in order)

1. Get started with generative AI and agents
The concepts module. What an agent actually is, how it differs from a plain chatbot, where tools and memory fit. Beginner-friendly, no setup. Start here even if you've used ChatGPT every day — using AI and understanding agents are different skills.
https://learn.microsoft.com/en-us/training/modules/get-started-with-generative-ai-and-agents/?wt.mc_id=studentamb_681095

2. Develop an AI agent with Semantic Kernel
The hands-on one. You build a working agent with Microsoft's Semantic Kernel instead of just reading about agents. This is the module that turns "I've watched tutorials" into "I've built one" — the thing you can actually say in an interview.
https://learn.microsoft.com/en-us/training/modules/develop-ai-agent-with-semantic-kernel/?wt.mc_id=studentamb_681095

3. Connect agent to MCP tools
The level-up. MCP (Model Context Protocol) is how agents plug into real tools and services. This module connects your agent to that world — it's where toy demos end and useful agents begin.
https://learn.microsoft.com/en-us/training/modules/connect-agent-to-mcp-tools/?wt.mc_id=studentamb_681095

Why the badges matter more than you'd think

Each finished module lands a badge on your Microsoft Learn profile. On its own that's small. Stacked on a resume or a LinkedIn profile next to a project, it's verifiable proof you did the work — not a line you typed yourself, a credential Microsoft issued. For students heading into placements or internship interviews, that difference is real.

Who this is for (and who it isn't)

For: students and early-career devs who want agent skills without paying for a course, and anyone who learns better by building than by watching.
Not for: people who want a full ML theory foundation — this path is applied. Do your maths and ML basics elsewhere; come here to build.

My plan

I'm working through all three as part of my ambassador path requirements, and I'll update this post with honest notes after each module — what was easy, what was confusing, what I'd skip. If you start too, tell me in the comments where you got stuck. Chances are I got stuck there first.

— Shivam Yadav, BTech student & Microsoft Student Ambassadors (registered member)