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What You'll Learn

Understand Artificial Intelligence
Machine Learning
Generative AI
and Large Language Models (LLMs) from a Product Managers perspective.,Apply AI tools and prompt engineering to product discovery
customer research
competitive analysis
and everyday product management tasks.,Understand AI Agents
Agentic AI
RAG
embeddings
and AI workflows and identify appropriate use cases for AI-powered products.,Evaluate AI models
capabilities
limitations
hallucinations
data requirements
and performance tradeoffs to make informed product decisions.,Develop AI product strategies
roadmaps
PRDs
user stories
and feature requirements aligned with customer needs and business goals.,Measure AI product success using evaluation frameworks
quality metrics
KPIs
cost analysis
and business value assessments.,Apply Responsible AI principles
including privacy
bias
security
governance
transparency
and human oversight.,Build a practical AI product proposal through hands-on exercises and a real-world SaaS product management case study.

Requirements

No prior AI or Machine Learning experience required. This course starts with the fundamentals.,No coding or programming knowledge needed. All AI concepts are explained from a practical product management perspective.,Basic understanding of products
business processes
or customer needs is helpful but not mandatory.,A computer or laptop with an internet connection to access course materials and complete exercises.,Access to a free AI assistant or an approved AI tool is recommended for hands-on activities.,Familiarity with Agile
Scrum
or product management workflows is beneficial but not required.,A willingness to explore Generative AI
AI Agents
Prompt Engineering
and AI-driven product innovation.,No paid software
AI subscriptions
or API keys required.

Description

This course contains the use of artificial intelligence.

Master AI Fundamentals and Apply Artificial Intelligence to Real-World Product Management

Artificial Intelligence (AI) is changing how products are researched, designed, built, and delivered. For Product Managers, understanding AI is becoming an essential skill—not because every PM needs to become a data scientist or machine learning engineer, but because better AI knowledge leads to better product decisions.

Welcome to AI Fluency Foundations for Product Managers, a practical, beginner-friendly course designed to help you understand Generative AI, Large Language Models (LLMs), Machine Learning, AI Agents, and AI-Powered Product Development.

Whether you're an aspiring Product Manager, Product Owner, Senior Product Manager, or Product Leader, this course will help you confidently navigate the rapidly evolving world of AI Product Management.

What Will You Learn?

You'll develop a strong foundation in essential Artificial Intelligence concepts and discover how to apply them throughout the Product Management Lifecycle.

Key topics include:

AI Fundamentals: Understand Artificial Intelligence, Machine Learning, Deep Learning, Predictive AI, and Generative AI.
Large Language Models (LLMs): Explore tokens, context windows, model capabilities, hallucinations, and limitations.
AI Agents and Agentic AI: Understand autonomous workflows, tool use, AI assistants, and human-in-the-loop decision-making.
Prompt Engineering: Learn effective prompting techniques to improve productivity, research, analysis, and communication.
Retrieval-Augmented Generation (RAG): Understand embeddings, vector databases, semantic search, and knowledge-grounded AI.
AI Product Strategy: Identify AI opportunities, evaluate business value, and prioritize AI-powered features.
AI-Powered Product Discovery: Use AI for customer research, competitive analysis, market research, and user feedback.
AI Product Requirements: Create PRDs, user stories, acceptance criteria, and AI feature specifications.
AI Evaluation: Understand model performance, accuracy, reliability, latency, cost, and quality metrics.
Responsible AI: Explore AI ethics, governance, privacy, security, bias, transparency, and risk management.
AI Product Roadmaps: Evaluate opportunities and plan AI adoption, experiments, and product launches.

Learn Through Practical Product Management Scenarios

This isn't another course filled with complicated algorithms or abstract technical explanations.

You'll work through BrightDesk, a realistic SaaS customer support case study, applying AI concepts to everyday product challenges.

Through hands-on exercises, practical assignments, decision frameworks, and product management templates, you'll practice evaluating AI solutions, writing product requirements, identifying risks, and developing an AI product strategy.

You'll also complete a capstone project that brings together AI fundamentals, product discovery, feature prioritization, evaluation, and launch planning.

Who Should Take This Course?

This course is ideal for Product Managers, Associate Product Managers, Product Owners, Technical Product Managers, Product Leaders, Business Analysts, Product Consultants, and professionals transitioning into AI Product Management.

No programming experience, machine learning background, or advanced mathematics is required.

Why Enroll?

The future of product management isn't simply about adding AI features. It's about knowing when AI creates genuine customer value, how to evaluate its limitations, and how to make informed product decisions.

Build your AI literacy, Generative AI fluency, AI strategy skills, and product leadership confidence through practical examples you can apply immediately.

Start building the AI fluency every modern Product Manager needs!

Who this course is for:

Aspiring Product Managers who want to develop AI fluency and prepare for AI-focused product management opportunities.,Associate and Junior Product Managers looking to understand AI fundamentals and apply AI to daily product management activities.,Product Managers and Product Owners who want to use Generative AI for research
requirements
prioritization
and decision-making.,Senior Product Managers and Product Leaders responsible for evaluating AI opportunities
defining AI product strategies
and managing AI-powered features.,Technical Product Managers who collaborate with AI engineers
data scientists
and development teams on AI-driven products.,Business Analysts and Product Consultants interested in AI use cases
business process improvement
and intelligent automation.,Entrepreneurs and Startup Founders exploring how to integrate AI capabilities into digital products and SaaS platforms.,Professionals transitioning into AI Product Management who want practical AI knowledge without learning advanced programming or machine learning mathematics.