AI Free course · Certificate included
Building AI Products & Workflows
From use-case discovery to production: prototyping, models, orchestration, privacy, evaluation, economics, UX and regulation
- Advanced
- 7 h 1 min
- 18 lessons in 7 modules
- 2 h 36 min of video lectures
- Updated Sep 2026
About this course
Most AI initiatives stall between an impressive demo and dependable daily use. This advanced course is for product managers, operations leads, founders and team heads who decide what gets built and make it work. You will find and scope high-value use cases, prototype on real data with spreadsheets and AI coding tools, and decide whether to build, buy or blend. You will choose models per route, orchestrate reliable workflows and integrate AI with the systems you already run, including through MCP. You will design privacy-aware, secure data flows, run evaluation-driven development, monitor quality, cost and drift, model cost per successful outcome, and design trustworthy UX for both suggestions and agentic actions. Finally, you will turn the 2026 regulatory landscape into product requirements, set up proportionate governance and scale adoption. Hands-on templates, prompts and code throughout.
Tools you’ll use
- Claude API
- Message Batches API
- Model Context Protocol
- OpenTelemetry
- FastAPI
- Pydantic
- n8n
- Claude Code
- GitHub Copilot
- Cursor
Skills
- AI product management
- AI strategy
- Evaluation-driven development
- AI governance
- AI UX design
- Data privacy
- Build vs buy
- AI workflow orchestration
What you’ll be able to do
- Identify, prioritise and scope high-value AI use cases with clear success and kill criteria
- Prototype on real data with spreadsheets and AI coding tools, and decide build, buy or blend
- Choose models per route and design orchestrated, well-integrated AI workflows that can change
- Design privacy-aware data flows and mitigate AI-specific security and vendor risks
- Run evaluation-driven development and monitor quality, cost, user signals and drift
- Model cost per successful outcome and design trustworthy UX for suggestions and agentic actions
- Turn 2026 AI regulation into product requirements and scale adoption with proportionate governance
Curriculum
Syllabus
- Modules
- 7
- Lessons
- 18
- Reading time
- 3.5 h
- Assessment questions
- 30
Identify where AI creates real value, prioritise ruthlessly, and define success before anything is built.
- Finding high-value AI use casesVideo lecture, 9′Video · 12 min
- Scoping and defining successVideo lecture, 9′11 min
Validate ideas quickly with prototypes, including AI coding tools, and decide whether to build, buy or blend.
- Rapid prototyping of AI featuresVideo lecture, 9′11 min
- Prototyping with AI coding tools and app buildersVideo lecture, 9′13 min
- Build vs buy (and blend)Video lecture, 9′12 min
Choose models and design an architecture that can change, orchestrate multi-step AI workflows reliably, and integrate AI into the systems you already run.
- Choosing models and an architecture that can changeVideo lecture, 9′14 min
- Workflow orchestration patterns for AI featuresVideo lecture, 9′14 min
- Integrating AI into existing systemsVideo lecture, 8′14 min
Design how data flows through AI features, protect privacy, and manage security and vendor risk.
- Data and privacy architecture for AI featuresVideo lecture, 9′12 min
- Security threats and vendor risk for AI featuresVideo lecture, 9′11 min
Make evaluation the engine of development, and monitor AI features in production for quality, drift and incidents.
- Evaluation-driven developmentVideo lecture, 8′12 min
- Monitoring AI features in productionVideo lecture, 8′11 min
Model and control the costs of AI features, and design experiences that build calibrated trust, including features where AI acts for users.
- Unit economics of AI featuresVideo lecture, 8′11 min
- UX patterns for AI featuresVideo lecture, 9′12 min
- Designing agentic product features users can trustVideo lecture, 9′13 min
Govern AI features proportionately, turn 2026 regulation into product requirements, drive adoption and scale from pilots to a portfolio.
- Operational AI governance for product teamsVideo lecture, 8′12 min
- AI regulation for product teams (2026 update)Video lecture, 9′14 min
- Driving adoption and scaling from pilot to portfolioVideo lecture, 8′11 min
- Final assessment
Your certificate
Finish with a credential anyone can check
Earn the Certified AI Product Builder badge: The holder can take AI features from idea to dependable production use: discovering and scoping use cases, prototyping with evidence, choosing models and orchestration patterns, integrating AI with existing systems, designing privacy-aware and secure architectures, running evaluation-driven development and monitoring, managing unit economics and trustworthy UX, and meeting current regulation with proportionate governance.
Completed all lessons and scored at least 80% on the final assessment.
- A public verification page
- A PDF certificate to download
- An Open Badge you can share
- One click to your LinkedIn profile
Final assessment
- 30questions drawn from a larger pool
- 45 mintime limit
- 80%pass mark
- 3attempts per 24 hours
Start learning today. It’s free.
Every lesson is free to read. A free account saves your progress, unlocks the final assessment and issues your certificate.