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Foundations of AI in Product Development

Introduction to AI in Product Management

Key AI Terminology for Product Teams

🎮 Crossword: AI Terminology Review

The Product Development Lifecycle (PDLC) Overview

AI in Ideation and Research

Using AI for Market Research

AI-Assisted Ideation and Brainstorming

AI in Design and Development

AI Tools for Prototyping and Design

Understanding AI in Software Development

AI in Testing and Launch

Automated Testing with AI

Ethical Considerations for AI Products

Quiz Section

Quiz: Foundations of AI

Quiz: Market Research and Ideation

Quiz: Design and Development Tools

Quiz: Testing and Ethics

Final Comprehensive Quiz

Course Feedback

Course Survey

AI Essentials for the Product Development Lifecycle is a practical, no-jargon course designed for product managers, designers, engineers, and cross-functional leaders who want to confidently integrate AI across every stage of the PDLC—from ideation to launch. You’ll learn how AI differs from traditional software, where it adds the most value, and how to apply it responsibly. Through clear explanations, real-world examples, hands-on exercises, and quick quizzes, you’ll build a working vocabulary of AI concepts like machine learning, NLP, predictive vs. generative AI, and training data. Then, you’ll put those concepts to work: use AI to accelerate market research, synthesize customer feedback, brainstorm features, generate wireframes, create prototypes, document code, and automate testing. We’ll also cover ethical guardrails, including bias, privacy, and transparency, so you can ship AI features with confidence. Whether you’re AI-curious or already experimenting, this course gives you a structured playbook to boost team velocity, reduce risk, and deliver AI-enabled products that customers love.

AI Essentials for the Product Development Lifecycle

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            <p>The integration of Artificial Intelligence into the product development lifecycle represents a fundamental shift in how modern digital solutions are conceived, built, and maintained. This course provides a comprehensive exploration of AI essentials, beginning with the foundational concepts that distinguish AI-enabled products from traditional software architectures. Participants will examine key terminology—including Machine Learning, Natural Language Processing, and Generative AI—to establish a technical baseline necessary for effective cross-functional collaboration. By understanding the "AI-First" strategy, product professionals can better identify high-impact opportunities within the standard stages of the development lifecycle, ensuring that technological capabilities align with strategic business objectives.</p>

<p>Beyond theoretical foundations, this curriculum delves into the practical application of AI tools across research, design, and quality assurance. The modules demonstrate how AI-driven market analysis and automated prototyping can significantly accelerate time-to-market while enhancing the precision of user personas and feature ideation. Furthermore, the course addresses the critical technical and moral responsibilities inherent in deploying AI, such as mitigating algorithmic bias, ensuring data privacy, and maintaining transparency. Through a rigorous examination of automated testing and ethical frameworks, learners will gain the insights required to launch reliable, responsible, and innovative products in an increasingly automated landscape.</p>
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