C11. LLM Practitioner Certified PM (AI PM Learning Program)

A complete path: lessons, projects, certification, support, and your digital PM portfolio

Hey, Paweł here. I’m excited to share the first module of our AI PM Learning Program, Large Language Models.

This is where you’ll build your foundation in LLMs, from prompts to RAG to fine-tuning to basic evals.

It’s split into:

• C10. LLM Foundations Certified PM: Demonstrated knowledge and took the exam

• C11. LLM Practitioner Certified PM: Demonstrated a real experience by building AI products

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Updated on 10/6/2025. More information about the split in the recent post:

C10. LLM Foundations Certified PM

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LLM Foundations/Practitioner PM

Here’s the exact set of lessons covering the scope you need:

• Lesson 1: Introduction to AI Product Management

  • Scope: Neural networks, transformers, LLMs, decoders, encoders, tokenization, reinforcement learning, loss function, self-attention, model weights.

• Lesson 2: Prompt Engineering: 14 Prompting Techniques Every PM Should Know

  • Scope: Prompt engineering

• Lesson 3: Step-by-Step: Three Essential APIs to Interact With LLMs

  • Scope: Completion API, Responses API, OpenAI Platform, streaming

  • Tools: Lovable and Supabase or Replit and SQL

• Lesson 4: A Guide to Context Engineering for PMs (none of the points is agent-specific, all can be applied to LLMs, too)

  • Scope: Prompt engineering, RAG architectures, short-term memory, long-term memory, how LLMs call and receive tool results

• Lesson 5: How to Build a RAG Chatbot Without Coding

  • Scope: Vector stores, embeddings, chunking, RAG, LLM workflows

  • Tools: Lovable, Pinecone, Supabase, OpenAI Platform, n8n

• Lesson 6: The Ultimate Guide to Fine-Tuning for PMs

  • Scope: RL vs. Fine-Tuning, SFT, DPO, ORPO, KTO

  • Tools: OpenAI or Hugging Face

• Lesson 7: The Ultimate Guide to AI Observability and Evaluation Platforms

  • Scope: Observability, Rule-based evals, LLM-based evals

  • Suggested tool: PromptLayer

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How to Earn the LLM Foundations Certified PM

All you need to do is to take a free knowledge test:

• 20 single-choice questions

• 80% required to pass

• 1 attempt per week (a larger pool of questions)

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How to Earn the LLM Practitioner Certified PM

Step 1: Earn the LLM Foundations Certified PM

Step 2: Implement a set of hand-on projects:

1. Implement one selected LLM chatbot (Lesson 3). Then:

   1. Add observability (Lesson 7),

   2. Add one role-based and one LLM-as-judge eval (Lesson 7).

2. Fine-tune a model (Lesson 6) - can be combined with the previous project.

3. Build a standard RAG chatbot (Lesson 5).

Submit all three projects together to pawel@productcompass.pm with “C11” in the subject.

Questions?

In case of any questions or doubts, you get full support on our Slack:
#c11-llm-practitioner-pm

Link to join our community: Your Premium PM Resources

I’m also available during weekly office hours.

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More About Certificates

After completing each track (e.g., C10, C11), you will get a digital, shareable certificate.

Currently, a student’s public profile looks like this: https://www.accredia.io/users/pawel-huryn

I’m also working on extending accredia.io, so that each certificate can be accompanied by a set of digital assets: your digital PM portfolio. That way, you can demonstrate things you actually implemented beyond taking a quiz.

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More Resources & Why Learn With Me

Extra resources

Beyond the lessons, here are some additional resources to explore:

• AI Product Manager Glossary - understand key terms

• TensorFlow Playground - play with neural networks

• Anthropic Prompt Engineering - my go-to resource

• Interactive RAG Simulator - study common RAG architectures visually

• AI PM Learning Roadmap - extra links, guides, and resources (optional)

Why learn with me?

Of course, resources alone aren’t enough - you need support. So why learn with me?

I bring 11+ years of PM experience, including running a successful B2B startup.

But what matters most is practice: rolling up your sleeves is the only way to truly retain knowledge. I’m the only PM author here who spends most of my time actually researching and building with AI - and connecting the two worlds: Product & AI.

I also work closely with Miqdad Jaffer (Product Lead, OpenAI) as an AI Labs Build Leader, and I help AI PM Certification students (#1 AI PM Cohort on Maven) crush their Capstone Projects with demos, live Q&A, and async support.

(30-day money-back guarantee. Many members expense it through their company’s learning budget.)

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P.S. You might also check the next module:

C21. AI Agents Practitioner PM (AI PM Learning Program)