Product Management with AI

Product Management with AI

Instructor: AI CERTs Team

Access provided by Vanderbilt University

9 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

9 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Understand AI Applications in Product Management: Explore how AI supports product planning, customer analysis, and roadmap development.
Evaluate AI Product Analytics Tools: Assess AI tools that improve user research, product insights, and faster analysis workflows.
Strengthen Product Research and Planning: Apply AI-supported approaches to improve roadmap prioritization and product decision accuracy.
Implement AI-Driven Product Strategies: Identify AI opportunities that strengthen customer insights and strategic business outcomes.

Skills you'll gain

Tools you'll learn

AI Workflows

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments

Taught in English

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There are 9 modules in this course

Artificial intelligence is changing how product teams plan roadmaps, evaluate customer needs, and improve product decisions across business environments. Organizations are increasingly using AI-powered tools to accelerate research, improve analysis, and strengthen product planning workflows.

This Product Management with AI course is designed for product managers, founders, business professionals, and learners seeking practical knowledge of AI in product environments. Learners will explore how AI technologies support user research, product analytics, roadmap planning, and customer insight generation without requiring advanced technical expertise. The course focuses on implementation-oriented product management applications and modern business workflows. You’ll examine how AI tools support feature prioritization, market evaluation, product optimization, and strategic analysis. Through practical scenarios, learners will explore how AI supports product discovery, analytics interpretation, workflow efficiency, and faster research processes. You’ll also learn how professionals evaluate AI opportunities, improve planning accuracy, and support responsible AI use across product environments. In addition, the course introduces foundational concepts around AI governance, ethical AI adoption, and implementation approaches used within modern product teams. By the end of the course, you’ll be able to identify AI opportunities in product management, improve roadmap prioritization, accelerate product research workflows, strengthen customer insight generation, and apply AI-supported approaches to improve strategic decision-making. Enroll in this AI product management course to build practical product strategy skills and support modern product operations with greater confidence.

This module introduces the fundamentals of Artificial Intelligence and its impact on modern product management. Learners explore key AI concepts, applications, and opportunities for integrating AI into product strategies. The module helps product managers understand how AI can support innovation and business value creation.

What's included

7 videos1 assignment1 plugin

7 videosTotal 34 minutes

Course Introduction4 minutes
1.1 What is AI?3 minutes
1.2 Branches of Artificial Intelligence6 minutes
1.3 Deep Dive into AI Applications for Product Management6 minutes
1.4 The Role of an AI Product Manager4 minutes
1.5 Introduction to the Importance of AI in Product Development4 minutes
1.6 Challenges of AI in Product Development6 minutes

1 assignmentTotal 30 minutes

Quiz 130 minutes

1 pluginTotal 5 minutes

Activity: Tab5 minutes

This module explains the core concepts and principles of Machine Learning used in AI-powered products. Learners explore different learning approaches, data requirements, and model development processes. The module builds foundational knowledge to help product managers collaborate effectively with AI teams.

What's included

7 videos1 assignment1 plugin

7 videosTotal 29 minutes

2.1 Introduction to Machine Learning4 minutes
2.2 How Machine Learning Works3 minutes
2.3 Types of Machine Learning5 minutes
2.4 Comparison of Supervised, Unsupervised, and Reinforcement Machine Learning5 minutes
2.5 Why We Need Data Preprocessing4 minutes
2.6 Data Preprocessing Steps in Machine Learning5 minutes
2.7 Consequences of Ignoring Data Preprocessing4 minutes

1 assignmentTotal 30 minutes

Quiz 230 minutes

1 pluginTotal 5 minutes

Activity: Case Study5 minutes

This module covers the complete lifecycle of developing AI-driven products, from ideation to deployment. Learners understand data preparation, model development, testing, and continuous improvement processes. The module enables product managers to effectively plan and manage AI product initiatives.

What's included

8 videos1 assignment1 plugin

8 videosTotal 28 minutes

3.1 The Integration of AI into Product Development4 minutes
3.2 Role of AI in Product Development4 minutes
3.3 AI Transforming Product Development4 minutes
3.4 Merits of AI in Product Development3 minutes
3.5 Different Stages of AI Product Development2 minutes
3.6 Use Cases of AI for Product Development in Different Industries3 minutes
3.7 Methods for Prototyping and Testing AI-Driven Products5 minutes
3.8 Best AI Tools for Product Managers4 minutes

1 assignmentTotal 30 minutes

Quiz 330 minutes

1 pluginTotal 5 minutes

Activity: Sequence5 minutes

This module explores ethical considerations involved in designing and deploying AI products. Learners understand AI bias, fairness, transparency, privacy, and responsible AI practices. The module helps product managers create trustworthy AI solutions that align with user and organizational values.

What's included

10 videos1 assignment1 plugin

10 videosTotal 33 minutes

4.1 Bias, Fairness, and Privacy Protection3 minutes
4.2 Transparency, Explainability, and Responsibility3 minutes
4.3 Safety, Reliability, and Social Impact3 minutes
4.4 Regulatory Compliance, Ethical Decision-Making, and Continuous Monitoring4 minutes
4.5 Bias: What It Is, Its Sources, and the Possibility of Eliminating It4 minutes
4.6 Strategies for Identifying and Addressing Bias in AI Algorithms and Products6 minutes
4.7 Key to Fix Bias in AI and Machine Learning Algorithms3 minutes
4.8 Tools to Reduce Bias: AI Fairness 3603 minutes
4.9 Tools to Reduce Bias: IBM Watson Open Scale and Google’s What-If Tool2 minutes
4.10 Examples: What Are Some Real-World Examples of AI Bias?3 minutes

1 assignmentTotal 30 minutes

Quiz 430 minutes

1 pluginTotal 5 minutes

Activity: Problem Statement5 minutes

This module focuses on strategies for successfully implementing AI solutions within products and organizations. Learners explore AI adoption approaches, integration methods, and common implementation challenges. The module helps product managers plan effective AI initiatives that deliver measurable outcomes.

What's included

10 videos1 assignment1 plugin

10 videosTotal 42 minutes

5.1 Steps for AI Integration and Product Enhancement6 minutes
5.2 Identifying Suitable AI Technologies and Preparing Your Data for AI Integration3 minutes
5.3 Implementing AI in Your Product and Selecting Tools & Frameworks6 minutes
5.4 Developing AI Models and Deploying AI Features4 minutes
5.5 Monitoring and Improving AI Performance3 minutes
5.6 Examples of AI Integrations3 minutes
5.7 Methods to Integrate AI into an App3 minutes
5.8 Key Steps and Strategies in Stakeholder Management for Product Teams5 minutes
5.9 Benefits and Role of Stakeholders in Product Management5 minutes
5.10 What Is It That Stakeholders Really Want?4 minutes

1 assignmentTotal 30 minutes

Quiz 530 minutes

1 pluginTotal 5 minutes

Activity: Carousel5 minutes

This module explains how to measure and evaluate the performance of AI-powered products. Learners explore key metrics, evaluation methods, and approaches for monitoring AI system effectiveness. The module enables product managers to make data-driven decisions and improve AI product performance.

What's included

9 videos1 assignment1 plugin

9 videosTotal 44 minutes

6.1 KPI: Introduction, Evolution, and Common KPIs for AI in Marketing7 minutes
6.2 AI-Enhanced Tracking of KPIs4 minutes
6.3 Examples of AI Tools for KPI Measurement and Analytics3 minutes
6.4 Case Studies in AI-Driven KPI Measurement6 minutes
6.5 KPI Dashboard Software and Tools6 minutes
6.6 Introduction to Performance Evaluation3 minutes
6.7 Techniques Used for Performance Evaluation: Confusion Matrix5 minutes
6.8 Techniques Used for Performance Evaluation: AUC-ROC Curve6 minutes
6.9 Techniques Used for Performance Evaluation: Gini Coefficient and R-Squared/Adjusted R-Squared4 minutes

1 assignmentTotal 30 minutes

Quiz 630 minutes

1 pluginTotal 5 minutes

Activity: Drag and Drop5 minutes

This module introduces the regulatory and compliance requirements associated with AI development and deployment. Learners explore topics such as data protection, AI standards, risk management, and compliance practices. The module helps product managers understand the importance of building compliant AI products.

What's included

9 videos1 assignment1 plugin

9 videosTotal 40 minutes

7.1 Introduction to the Regulatory Landscape: AI Regulations Across Different Countries6 minutes
7.2 Key Global Regulations4 minutes
7.3 Key Regulatory Rules Required for AI4 minutes
7.4 Entities Most Adversely Affected by AI Regulations3 minutes
7.5 Impact on AI Companies3 minutes
7.6 Introduction to AI Regulatory Compliance5 minutes
7.7 Compliance Strategies5 minutes
7.8 Role and Importance of Data Privacy in AI Compliance6 minutes
7.9 The Role of Legal Professionals in Ensuring Compliance with AI Regulations5 minutes

1 assignmentTotal 30 minutes

Quiz 730 minutes

1 pluginTotal 5 minutes

Activity: Hotspot5 minutes

This module explores emerging AI trends and their influence on the future of product management. Learners discover advancements in AI technologies, evolving product strategies, and new opportunities for AI-driven innovation. The module prepares product managers to adapt to future AI developments and market changes.