Certification
Certification in Designing, Managing & Evaluating LLM Products with RAG & Agents
Get certified in AI Product Management for LLMs, RAG, agents, and evaluations. Prove you can ship reliable AI features, pick smart trade-offs, design prompts, run fine-tunes, implement RAG, deploy agents, and build evals that keep products honest.
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 15 chapters of the course
20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.
- 01AI product management and LLMs14:04
- 02Stages of LLM training10:42
- 03Transformers and GPUs13:55
- 04Post-training, hallucinations and the value chain18:20
- 05Case study: AI note takers8:53
- 06How meeting tools work and growth16:18
- 07RAG16:24
- 08Prompt engineering essentials11:52
- 09Prompting for busy people16:16
- 10Prompt techniques21:26
- 11Fine-tuning and transfer learning10:46
- 12Creating AI agents15:10
- 13Guardrails17:10
- 14Evaluating AI products14:12
- 15Building an AI portfolio6:23
The AI Product Management Course: LLMs, RAG, AI Agents, Evaluations (Video Course) is a certification designed to help you ship AI features with confidence in just 3.5 hours. You'll learn to make the right trade-offs, apply prompt engineering, RAG, fine-tuning, and agents, and build evaluations,unlocking Increased Productivity, Competitive Advantage, Improved Decision-Making, and a Future-Proof Career. Enroll to move your product from demo to dependable, fast.
This certification covers the following topics:
- LLM fundamentals and the three-stage training process
- Transformers, GPUs, and the modern GenAI stack
- The GenAI value stack and product manager roles
- Context engineering and prompt engineering techniques
- Retrieval-Augmented Generation (RAG): design and real-world implementation
- Fine-tuning: when to use it, data strategy, and deployment
- AI agents: design patterns, tools, and guardrails
- Evaluations (evals): rubrics, metrics, and automated testing
- PM decision framework: Prompting vs. RAG vs. Fine-tuning
- Cost, latency, and reliability considerations
- Product strategy, discovery/delivery workflows, and risk management
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.