Generative AI for Product Managers Specialization Course Syllabus

Master the end-to-end lifecycle of building and scaling generative AI products as a product manager. This specialization equips PMs with practical frameworks, vendor-neutral insights, and real-world templates to lead AI initiatives from strategy to deployment. With approximately 13 weeks of content, learners invest 3–5 hours per week through hands-on projects, case studies, and AI co-creation exercises—culminating in a go-to-market capstone. Lifetime access ensures ongoing relevance in this fast-evolving domain.

Module 1: GenAI Foundations for PMs

Estimated time: 16 hours

• Transformer architecture basics for non-technical PMs
• Understanding cost vs. performance tradeoffs in LLMs
• Vendor selection criteria: OpenAI, Anthropic, and open-source models
• Case Study: Notion AI implementation and lessons learned

Module 2: GenAI Product Design

Estimated time: 20 hours

• User story generation using AI tools
• Prototyping UI concepts with Midjourney and DALL-E
• Conversational UI best practices for chatbots and agents
• Hands-on: Build a feature specification using ChatGPT

Module 3: Prompt Engineering for Product Requirements

Estimated time: 12 hours

• Writing effective prompts for user scenarios
• Iterating on prompt outputs with AI pair programming
• Validating prompts against product goals
• Template: Prompt requirement documentation (PRD) section

Module 4: LLM Integration Patterns

Estimated time: 14 hours

• API-based integration strategies for GenAI features
• Fine-tuning vs. retrieval-augmented generation (RAG)
• Security and latency considerations in deployment
• Architecture patterns for scalable AI products

Module 5: Scaling GenAI Products

Estimated time: 16 hours

• Monitoring for model drift and performance decay
• Designing feedback loops for continuous improvement
• Compliance and regulatory checklists (GDPR, AI Act)
• Ethical AI implementation frameworks and risk assessment

Module 6: Final Project

Estimated time: 20 hours

• Develop a comprehensive go-to-market strategy for a GenAI product
• Create an ethical review checklist and risk mitigation plan
• Deliver a final presentation with AI-coconstructed prototypes and specs

Prerequisites

• Familiarity with basic product management principles
• Experience writing user stories or PRDs preferred
• Basic understanding of software development lifecycle

What You'll Be Able to Do After

• Develop a GenAI product strategy aligned with business goals
• Apply prompt engineering techniques to define product requirements
• Design and prototype AI-powered features using generative tools
• Implement ethical and compliant GenAI solutions using structured frameworks
• Lead scaling efforts for GenAI products with monitoring and feedback systems