Master AI-powered product management for the workloads that cannot fail — from strategy and discovery to roadmap, launch, and growth. Taught by operators who have spent decades shipping products and AI capabilities inside the global ten thousand enterprises. Build AI as a real capability, not a demo, and lead cross-functional teams through the transformation.
Leading product teams and need to integrate AI capabilities into existing products and roadmaps.
Want to level up with AI fluency and build an AI-powered PM toolkit that differentiates them.
Already work with engineering teams and want deeper understanding of AI/ML product patterns and trade-offs.
Building AI-native products and need structured PM frameworks to ship faster and more strategically.
Define what to build, for whom, and why — with AI as both the tool and the product capability.
Most PMs bolt AI features onto their product because leadership says "add AI." This course teaches you to think from first principles — identifying where AI creates genuine user value, validating with AI-powered research at 10x speed, and building product strategies that are defensible and differentiated. You'll learn to evaluate build-vs-buy-vs-partner decisions, understand AI model trade-offs, and write PRDs that engineering teams actually want to build.
Align engineering, design, data science, and leadership around an AI product vision they can execute.
AI products break traditional PM processes. Sprint planning doesn't work when model training takes weeks. Stakeholder alignment collapses when nobody can explain why the AI "sometimes gets it wrong." This course teaches you to build AI-specific roadmaps, manage uncertainty, communicate trade-offs, and lead cross-functional teams where data scientists, ML engineers, and product designers all need different things from you.
Launch AI features that users trust, adopt, and love — then scale them.
Launching AI products is fundamentally different from launching traditional features. Users need to understand what AI is doing, trust that it works, and recover gracefully when it doesn't. This course teaches you to design AI onboarding experiences, build feedback loops that improve models, manage the cold start problem, and create growth flywheels powered by AI. You'll also learn pricing and packaging for AI features — usage-based, tiered, and value-based models.
Define where AI creates genuine value, validate with users, and build an AI product strategy that engineering, design, and leadership can rally behind.
Build AI-specific roadmaps, communicate trade-offs, and lead cross-functional teams through the unique challenges of AI product development.
Ship AI features users trust, design feedback loops that improve your models, and build growth flywheels that compound over time.
A comprehensive AI opportunity assessment and product vision document for your current org or a product you want to build.
Templates and frameworks for writing product requirements that ML engineers, data scientists, and designers can execute on.
RACI matrices, communication templates, and stakeholder alignment frameworks tailored for AI product teams.
A complete AI feature launch playbook covering onboarding, trust design, feedback loops, and go-to-market.
A defensible AI pricing and packaging model with competitive analysis and revenue projections.
Complete all 3 courses + capstone to earn the AI Impact Foundation Product Management Track Professional Certification.
AI Product Strategy & Discovery
AI Roadmapping & Cross-Functional Leadership
AI Product Launch & Growth
No. This track is built for product people, not engineers. You'll learn enough about AI/ML concepts to make informed product decisions and communicate effectively with technical teams, but you won't be writing code or training models.
Not at all. Course 1 covers foundational AI product strategy, but Courses 2 and 3 go deep into cross-functional leadership, responsible AI governance, AI pricing models, and growth mechanics that even experienced PMs rarely get formal training on.
AI Impact Essentials is recommended if you're new to AI. If you already use AI tools daily and understand concepts like LLMs, prompt engineering, and model limitations, you can jump directly into the Product Managers track.
Each course is a 3-day intensive — roughly 6–8 hours per day across video lessons, project work, and live sessions. The format is built for working professionals who want a focused sprint rather than a slow weekly cadence.
Absolutely. Every deliverable is designed to be immediately applicable. Most students use their actual product or organization as the case study throughout the track, so you leave with real assets, not hypothetical exercises.
Yes. Every professional course enrollment directly funds a full scholarship for an underserved student through the AI Impact Foundation. You learn AI product management. A student gets access to AI education, a laptop, mentorship, and meals.