Generative AI for Product Owners Specialization Course Syllabus

Overview (80-120 words) describing structure and time commitment.

Module 1: Generative AI: Introduction and Applications

Estimated time: 7 hours

• Describe the difference between generative and discriminative AI
• Explore use cases of generative AI across text, code, image, audio, and video generation
• Identify key generative AI models and their capabilities
• Understand how generative AI applies to different stages of the product lifecycle

Module 2: Generative AI: Prompt Engineering Basics

Estimated time: 9 hours

• Explain core concepts of prompt engineering
• Apply best practices for writing effective prompts
• Use chain-of-thought and tree-of-thought prompting techniques
• Practice with interview-style prompting to improve AI output accuracy

Module 3: Generative AI: Revolutionizing the Product Owner Role

Estimated time: 8 hours

• Apply generative AI tools to analyze market trends and customer feedback
• Generate data-driven product roadmaps using AI insights
• Enhance stakeholder engagement through AI-powered communication
• Integrate AI into sprint planning and backlog prioritization

Module 4: Ethical Considerations in Generative AI Adoption

Estimated time: 4 hours

• Identify risks and biases in generative AI outputs
• Apply principles of responsible AI in product decisions
• Evaluate ethical implications in customer data usage

Module 5: Hands-on Lab: Applying GenAI Tools

Estimated time: 6 hours

• Practice with ChatGPT for user story generation
• Use Gemini for competitive analysis and insights
• Leverage Copilot for technical requirement drafting
• Experiment with Claude for stakeholder communication drafts

Module 6: Final Project

Estimated time: 5 hours

• Develop an AI-enhanced product backlog using prompt engineering
• Create a strategic roadmap informed by AI-generated market insights
• Submit a reflection on ethical considerations and stakeholder alignment

Prerequisites

• Intermediate experience as a Product Owner or in Agile product development
• Familiarity with basic product lifecycle concepts and backlog management
• Basic understanding of AI and machine learning concepts preferred

What You'll Be Able to Do After

• Describe the capabilities and limitations of generative AI in product development
• Apply prompt engineering techniques to improve product planning and insights
• Use leading generative AI tools to enhance backlog management and strategy
• Drive stakeholder engagement using AI-generated content responsibly
• Integrate ethical AI practices into product decision-making processes