Certification
Certification in Leading AI Product Development
Become certified in AI Product Management and prove you can own AI products end-to-end. You'll know how to select models, build evals, set guardrails, and manage the economics,skills that show up in interviews and real roadmaps.

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.
- 01Welcome4:08
- 02Agenda2:21
- 03The AI PM mindset2:36
- 04Probabilistic versus deterministic3:52
- 05AI applications versus AI PM3:28
- 06AI-native versus AI-feature PMs4:44
- 07The AI stack4:40
- 08Responsible AI and guardrails4:39
- 09Tokenization4:38
- 10Embeddings4:38
- 11Positional encoding2:18
- 12Self-attention6:52
- 13Probability and temperature7:53
- 14Top-p and top-k sampling5:42
- 15Q&A and wrap-up7:14
The Job-Ready AI Product Management Bootcamp | Product Space (Video Course) is a hands-on certification built for product managers who want to actually ship and own AI products, not just speak in buzzwords. You'll build practical skills that drive increased productivity, sharper decision-making, real competitive advantage, and a future-proof career with higher income potential, adaptability, and long-term growth. If you're serious about owning AI products end-to-end,from model selection and evals to guardrails and real business impact,this bootcamp is a straightforward way to get there and a strong signal to employers.
This certification covers the following topics:
- Probabilistic vs. deterministic product thinking and the mindset shift required for AI product management
- Distinguishing AI-assisted work from true AI product management and ownership
- Mapping the AI product role landscape across native, feature, and core AI products
- The modern AI stack and the essential technical fluency PMs need to be job-ready
- How large language models work, including the end-to-end generation pipeline
- Model selection, evaluation strategies, and defining success metrics for AI features
- Designing guardrails, safety layers, and responsible AI practices as core product requirements
- Economic modeling, cost structures, and operational trade-offs for AI products in production
- Experimentation, A/B testing, and data-driven decision-making for AI-powered experiences
- Job-ready artifacts, interview preparation, and career positioning for AI product roles
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.