AI for Product Management Bootcamp

Name: AI for Product Management Bootcamp
Rating: 4.1 (106 reviews)

Use the AI Canvas for applications from Health Tech to retail and fintech

Created byProf. Dr. Ana-Maria Olteteanu

Last updated 10/2026

English

English [Auto],

What you'll learn

Learn how to use the AI Product Canvas
Apply AI Product Canvas to predictive an generative AI
Explore 25+ real-world AI use cases across industries—from chatbots and fraud detection to medical triage and AI-generated onboarding flows.
Identify AI opportunities using both predictive and generative AI tools across real-world product use cases.
Frame predictive and generative AI into product management opportunities
Define data strategy essentials, including sourcing, labeling, privacy, and quality management, using industry-ready templates and checklists.
Learn from cutting-edge examples including facial recognition bias, predictive maintenance for IoT, knowledge base automation, and regulatory pitfalls in health
Discover exotic and emerging AI applications, such as AI for scent profiling, synthetic patient generation, and robotic fashion advisors, to inspire innovation
Evaluate and prioritize AI features based on user needs, business impact, and technical feasibility.
Write AI-ready Product Requirement Documents (PRDs) that specify data, model, evaluation metrics, and ethical considerations.
Understand regulatory and privacy challenges (GDPR, HIPAA) and how to design compliant AI systems from the ground up.
Evaluate generative AI features with a test set, a rubric and a launch bar before you ship.

Course content

7 sections • 33 lectures • 3h 23m total length

Why AI Changes Product Management10:17
Discover how artificial intelligence changes product management by making features probabilistic, requiring data-driven framing, robust data strategy, and ongoing ownership, with metrics like precision and recall, and clear risk communication.
The AI/ML Lifecycle in Plain English — with Generative AI Examples9:39
Navigate the five-stage AI lifecycle—from problem framing to deployment and monitoring—for both prediction and generative use cases, with the product manager guiding data strategies, experiments, and safeguards.
AI Industry trends& Job Expectations- Generative AI, Agents, No-Code Prototyping8:07
Explore 2025–2027 trends in generative ai, ai agents, and no-code prototyping, and learn to lead responsible product roadmaps with prompt design and ethical considerations.

AI Problem framing: From User Need to AI Prediction Problem8:22
Frame AI problems by translating user needs into a testable prediction task, using fraud detection to illustrate framing. Balance precision, recall, and business impact to guide thresholds and stakeholder decisions.
Problem-AI Fit Assessment (When Not to Use AI)8:11
Assess AI fit before building, identifying red flags like data quality and ROI, and prefer simple rules when value is limited.
AI Product Canvas Walkthrough8:35
the ai product canvas helps product managers align teams and turn big ideas into actionable plans using five core sections: user problem, task, data strategy, success metrics, and ethical considerations.
Churn Prediction in AI Product Canvas (Case Study)6:56
Apply the AI product canvas to churn prediction to align teams, define the 30-day churn probability, and identify data signals, then set ROC AUC, precision, and recall metrics with privacy.

Lead Scoring with AI Product Canvas7:16
Apply the product canvas to lead scoring by defining the 90-day conversion probability using signals from crm history, website interactions, and notes.
Inventory Demand Forecasting with AI Product Canvas6:38
Forecast inventory demand with an ai product canvas, using historical sales, promotions, weather, and holidays, across a suitable horizon, then evaluate with RMSE or MAPE against business KPIs.
Feature Adoption Prediction with AI Canvas6:31
Apply the AI canvas to predict feature adoption, using historical data, usage logs, and account attributes within 30 days to improve ROI while ensuring fairness and transparency.

Automated Customer Support with Generative AI Replies10:11
Apply the AI product canvas to automate customer support with a generative large language model, defining user problems, generation tasks, data, metrics, and ethical guardrails for safe, personalized email replies.
Personalized Email Drafting for Sales Teams with AI6:32
Automate personalized outreach emails for sales teams with AI, using CRM data and brand guidelines to boost open rates, consistency, and time saved.
Marketing Content Generation with Generative AI7:12
Discover how generative AI can scale marketing content across text, images, audio, and video while enforcing brand guidelines, optimizing data strategies, and boosting engagement.
Product Description AI Generation for E-commerce5:35
Automate scalable, on-brand product descriptions for e-commerce using AI, integrating structured specs, categories, and SEO keywords to boost readability, relevance, and conversions while upholding ethics.

Knowledge Base Article Drafting with Generative AI5:52
Draft knowledge base articles with generative AI from real support tickets to keep documentation fresh and SEO friendly. Use templates, ensure accuracy with human review, and track KPIs.
Creative Brainstorming Assistant with Generative AI8:39
Discover how a generative-ai driven creative brainstorming assistant partners with teams to generate diverse ideas, align outputs with brand guidelines, and measure impact through ethical, transparent AI.
Internal Knowledge Summarization with Generative AI8:44
Create tailored, audience-aware internal knowledge summaries from documents and meetings using a generative AI tool, ensuring data strategy, privacy, ethics, and transparency to enable faster, better-informed decisions.
Personalized Learning Path Generator9:59
Explore a personalized learning path generator using a product canvas to design data-driven, adaptive paths that tailor goals, assessments, and resources to individual learners.

Choosing Your First AI Feature3:32
What Makes an AI PRD Different4:17
Defining Data, Model and Metrics in the AI PRD4:18
Risk and Ethics in the AI PRD3:42
AI PRD Template Walkthrough5:26
AI PRD in Practice: Predictive Maintenance4:48
AI PRD in Practice: Sales Email Composer4:01
AI PRD in Practice: AI Learning Companion4:05
Evaluating Generative AI Before You Launch4:17
Bonus Lecture1:18
Practice deeper skills at AI for Happiness: increase your performance and wellbeing with 90+ tools and 50+ programs.

Four to start with (links open in your browser):
1. Pre-Mortem Analysis: https://aiforhappiness.com/tool/pre-mortem?try=1
2. Decide What's Next: https://aiforhappiness.com/tool/decide-next?try=1
3. First Principles Builder: https://aiforhappiness.com/tool/first-principles?try=1
4. Clarity: https://aiforhappiness.com/tool/clarity?try=1

More: https://aiforhappiness.com

If this course helped you, please leave a short, honest rating and review on the course page. It takes two minutes and helps other product managers find the course.

Requirements

No previous experience needed

Description

Are you a product manager, strategist, designer or tech leader who wants to use AI, but is not sure where to start? This bootcamp is a practical guide to understanding, planning and delivering AI-powered products. About 3.5 hours of short, story-led video lessons.

You will learn to use the AI Canvas to design useful, ethical and user-centered AI applications. The use cases come from familiar industries like health tech, edtech, fintech, mobility, customer support, B2B SaaS, productivity and retail, and from exotic AI use cases such as memory support for ADHD or emotion-sensitive design assistants.

We cover predictive AI, like lead scoring, fraud detection and feature adoption forecasting, and generative AI, like content drafting, onboarding chatbots and personalized learning material. Each use case is broken down into clear steps: who benefits, what data you need, what failure looks like and how success is measured.

New in this version:

Data Strategy for Product Managers. Why data is the product, how to plan data collection and labeling, privacy and regulation (GDPR, CCPA, HIPAA), and a 10-area data strategy checklist.
From Idea to AI-Ready PRD. Choose your first AI feature, write a PRD that covers data, model, metrics and risk, and see it applied in three worked use cases: predictive maintenance, a sales email composer and an AI learning companion. Includes the AI-Ready PRD Template as a download.
Evaluating generative AI before you launch: test sets, rubrics and a launch bar.
A Bonus Lecture with ways to keep practicing deeper skills.

Whether you are new to AI or want to deepen your PM skills, this course helps you go beyond buzzwords and build clever, usable and strategic AI products, for today's markets and tomorrow's possibilities.

If the course helps you, please leave a short, honest review. It helps other product managers find it, and it tells me what to improve.

Who this course is for:

Product Managers who want to design and lead AI-powered products with confidence and clarity.
Tech Leads and CTOs who want to frame generative use cases and de-risk AI development with smarter planning.
Founders seeking to translate customer problems into AI opportunities with strong business value.
UX Designers working on AI features who need to understand model behavior, data flows, and ethical risks.
AI/ML Engineers aiming to better align their work with real-world user needs and product goals.
Consultants advising on AI implementation and innovation strategies across industries.
Data Analysts contributing to AI projects who want to connect data strategy with product impact.
Professionals exploring AI who want a practical, structured introduction to building AI-powered products.
Product and project managers working in tech, SaaS, or digital transformation initiatives involving AI
Business leaders and strategists looking to integrate generative AI into their product or service lines.
Teams working on innovation, R&D, or digital transformation who need a shared language for AI development.
Aspiring AI practitioners from any background (design, data, dev, management) who want to connect AI concepts with real-world product work.
University and graduate students studying AI, data science, business, or HCI who want real-world product examples.
Professors and educators looking for frameworks and use cases to teach AI product development and strategy.
Startup founders and innovation consultants who need practical examples to shape AI offerings for clients or ventures

AI for Product Management Bootcamp

What you'll learn

Explore related topics

Course content

Foundations - AI for Product Managers3 lectures • 28min

AI Problem framing and the AI Canvas4 lectures • 32min

AI canvas applied to Prediction problems - From Lead scoring to Feature Adoption3 lectures • 20min

Generative AI Product management4 lectures • 30min

Data Strategy for Product Managers5 lectures • 21min

Generative AI New Use Cases - Practice the AI Canvas4 lectures • 33min

From Idea to AI-Ready PRD10 lectures • 40min

Requirements

Description

Who this course is for: