AI Product Management

Aim

Program Objectives

Program Structure

Week 1: Foundations of AI and Product Thinking

Module 1: Introduction to AI Product Management

• Chapter 1.1: Role of the AI Product Manager
• Chapter 1.2: How AI Products Differ from Traditional Software
• Chapter 1.3: AI Product Lifecycle Overview

Module 2: Fundamentals of AI & Machine Learning

• Chapter 2.1: AI/ML Basics for Product Managers
• Chapter 2.2: Types of Models (Supervised, Unsupervised, Generative)
• Chapter 2.3: Data Lifecycle and Its Impact on Products
• Chapter 2.4: Understanding Evaluation Metrics and Trade-offs

Week 2: Designing and Building AI Products

Module 3: From Use Case to Model

• Chapter 3.1: Identifying the Right AI Use Cases
• Chapter 3.2: Scoping MVPs for AI Capabilities
• Chapter 3.3: Working with Data, Labels, and Annotation
• Chapter 3.4: Model Selection and Collaboration with Data Science

Module 4: AI Product Design and UX

• Chapter 4.1: Designing for Explainability and Trust
• Chapter 4.2: Human-in-the-Loop Design Patterns
• Chapter 4.3: Feedback Loops and Active Learning
• Chapter 4.4: Ethical Considerations in AI Interfaces

Week 3: Deployment, Scaling, and Strategy

Module 5: AI Delivery and Product Operations

• Chapter 5.1: Model Deployment Workflows and Tools
• Chapter 5.2: A/B Testing and Monitoring in AI Systems
• Chapter 5.3: Managing Drift, Retraining, and Model Updates
• Chapter 5.4: Platform Choices and MLOps Integration

Module 6: Strategy, Roadmapping, and Stakeholder Management

• Chapter 6.1: Building an AI Product Strategy
• Chapter 6.2: Creating Roadmaps for Data-Driven Products
• Chapter 6.3: Managing Cross-Functional Teams in AI
• Chapter 6.4: Navigating Legal, Compliance, and Risk in AI

Who Should Enrol?

Program Outcomes

Fee Structure

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What You’ll Gain