Certification
Certification in Building and Architecting AI Agents
Become certified in building production-ready AI agents. You'll prove you can design tool loops, implement multi-step reasoning, and deploy functional agents that solve real problems,skills you can apply immediately.

The exam
Take the certification exam
Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.
What the exam covers
2 questions from each of the 9 chapters of the course
18 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.
- 01What agents really are1:53
- 02The building blocks5:22
- 03The four tiers1:10
- 04How to get good at this1:27
- 05Tier 1: no-code2:44
- 06Tier 2: low-code2:26
- 07Tier 3: agent harnesses2:42
- 08Tier 4: full code2:10
- 09How to pick a tier1:40
The Build AI Agents: A Practical Guide to Architecture & Tools certification is a hands-on video course that cuts through the hype and shows you what AI agents really are , a language model with tools in a loop. You'll walk away with the skills to build your own agents from scratch, giving you a serious competitive edge, a more future-proof skill set, and the confidence to make smarter decisions about AI in your work. If you've been hearing about AI agents and wondering how they actually work, this course is your chance to stop guessing and start building.
This certification covers the following topics:
- Chatbot vs. Agent: The Critical Distinction
- The Two Things That Make an Agent
- The Architecture of an Agent: Four Core Components
- The Agentic Loop: How Agents Actually Work
- Long-Term Memory: Vector Databases and RAG
- Tier One: No-Code Platforms
- Tier Two: Low-Code Platforms
- Tier Three: Agent Harnesses
- Tier Four: Full Code
- The Four Universal Decisions
- Choosing the Right Approach for Your Situation
Jobs this certification suits
Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.