Ship AI-powered products — strategy, roadmapping, user research, and go-to-market.
Never written code? You can still start here.
Module 0 opens with 18 lessons of programming from nothing — your first program, variables, loops, functions, reading errors, the terminal, Git and arrays — before any of the AI Product Management material. No prior coding assumed.
AI Foundations — optional basics (free)
Week 0 · 20 lessons
Beyond the chatbox: what AI assistants really are
How the model "thinks" — and why it changes how you ask
The capability map: what AI does brilliantly
The limits: hallucination, freshness, and what never to trust it with
Your first real win: turn a 30-minute task into 3
6 senior modules · 30lessons · capstone & certificate. Upgrade your plan to unlock the advanced tier.
Advanced AI Strategy & Platform Economics
5 lessons
Platform Thinking for AI Products
Network Effects & Data Moats in AI
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AI Product Spec Document
Competitive Analysis Report
User Research Plan
About
AI Product Management
20 questions · ~30 minutes
Context is everything: give it what it needs to know
Give it a role and a goal
Constraints and format: define what "good" looks like
Show, don't tell: examples and templates
Iterate like a pro: steer, don't restart
Documents and reports: summarise, extract, and draft better
Spreadsheets and data: Excel formulas, analysis, and charts
Presentations: from blank page to a solid deck
Long, messy input: transcripts, threads, notes, and screenshots
ChatGPT, Claude, Copilot, Gemini: which to reach for, and when
Make smarter decisions: AI as your thinking partner
Chaining steps: multi-part tasks done reliably
Your prompt library: reusable templates that save hours
Staying safe: privacy, accuracy, and company data
Capstone: do a real task end-to-end (graded) → your certificate
Module 0 — Foundations: How AI Works for Product Managers
Week 0 · 23 lessons
What a program is and how to run your first one
Storing values in variables, and why text and numbers behave differently
Making decisions with if, else and comparisons
Storing many values in a list
Looking things up by name with dictionaries
Doing something to every item with loops
Writing your own functions
Reading errors without panic
Finding the mistake in your own code
Saving your code in a file and running it
Importing code other people have written
Giving each project its own environment
Talking to your computer with the terminal
Saving your work with Git
Putting your work on GitHub
What an array is, and why a list is not enough
Picking out pieces: indexing and slicing, including two dimensions
Maths on a whole array at once, and where you go next
How AI Actually Works, for Product Managers
Data & the ML Lifecycle: Why AI Products Are Different
Measuring AI: Accuracy, Precision, Recall & the Tradeoffs
The Economics of AI Products & Prioritization
Responsible AI Foundations: Bias, Privacy & Governance
AI Product Foundations
Week 1 · 5 lessons
What Makes AI Products Different
AI Product Lifecycle
User Research for AI
Problem-Solution Fit
AI Feasibility Assessment
Strategy & Roadmap
Week 2 · 5 lessons
AI Product Strategy
Competitive Analysis
Roadmap Planning
Feature Prioritisation
OKRs for AI Products
Data & Requirements
Week 3 · 5 lessons
Data Requirements
Data Quality Assessment
ML Requirements Docs
Build vs Buy Decisions
Vendor Evaluation
Ethics & Governance
Week 4 · 5 lessons
AI Ethics Framework
Bias Detection & Mitigation
Fairness Metrics
Responsible AI
Regulatory Compliance
Design & UX
Week 5 · 5 lessons
AI UX Principles
Designing for Uncertainty
Explainability in UI
User Trust & Transparency
Error Handling UX
Go-to-Market
Week 6 · 5 lessons
GTM Strategy for AI
Pricing AI Products
Sales Enablement
Customer Education
Launch Planning
Metrics & Analytics
Week 7 · 5 lessons
AI Product Metrics
Model Performance KPIs
User Engagement Metrics
A/B Testing AI Features
Dashboard Design
Leadership & Scale
Week 8 · 5 lessons
Stakeholder Management
Cross-Functional Leadership
Scaling AI Products
Technical Debt Management
Building AI Teams
AI Product Portfolio Strategy
Competitive Dynamics in AI Markets
AI Business Model Design
Enterprise AI Governance & Compliance
5 lessons
The AI Regulatory Landscape
Enterprise AI Risk Frameworks
Responsible AI Program Design
AI Audit & Assurance
Enterprise AI Procurement & Vendor Management
Technical Depth for Product Managers
5 lessons
ML Pipeline Architecture for PMs
Model Lifecycle Management
LLM Integration Patterns
Data Architecture Decisions for AI Products
Infrastructure Cost Optimization for AI
Advanced Analytics & Experimentation
5 lessons
Causal Inference for Product Managers
A/B Testing at Scale
Metric Ecosystem Design
Advanced Cohort & Retention Analysis
Data-Driven Prioritisation Frameworks
Organizational Leadership & Change Management
5 lessons
Leading Cross-Functional AI Teams
AI Transformation Programs
Executive Communication for AI Products
Building AI Product Culture
Stakeholder Management at Scale
AI Product Portfolio & Capstone
5 lessons
AI Product Portfolio Management
M&A and Partnership Strategy for AI
International AI Product Expansion
Future of AI Product Management
Capstone: AI Product Strategy Masterplan