Master product strategy, data, and AI systems without writing code

What you'll learn
Differentiate clearly between Product Manager, Product Owner, and Project Manager roles—and explain how the AI Product Manager role uniquely operates
Identify and frame business problems that are suitable for AI and machine learning solutions, translating real-world needs into well-defined AI product
Design AI-ready product requirements and PRDs, including data dependencies, model constraints, evaluation metrics, and non-functional requirements
Collaborate effectively with data scientists, ML engineers, and platform teams by understanding the AI development lifecycle, model trade-offs
Evaluate and prioritize AI product decisions using data-driven trade-offs, balancing accuracy, business impact, user trust, operational cost, and scalability.
Plan and execute responsible AI product launches, incorporating MVP strategies, human-in-the-loop designs, monitoring plans, and ethical risk assessments.
Operate and iterate AI products in production, including monitoring model performance, handling data and model drift, and continuously improving product

Requirements
A basic understanding of business or product concepts, such as how companies build and sell products (no prior product management experience required).
Familiarity with technology or data concepts at a high level (e.g., knowing what data, software, or AI is—without needing to code).
Curiosity about AI, data, and how technology creates business impact, especially in modern digital products.
Basic computer skills, including using documents, spreadsheets, and presentation tools.

Who this course is for
Aspiring Product Managers who want to break into product roles focused on AI, machine learning, or data-driven products.
Traditional Product Managers looking to transition into AI or data science product teams and confidently work with ML engineers and data scientists.
Business analysts, consultants, and MBA students who want to move into AI-focused product leadership roles.
Engineers, data analysts, or data scientists who want to shift into product ownership and decision-making roles.
Startup founders and entrepreneurs building AI-enabled products and needing a strong product strategy foundation.
Professionals working with AI platforms (cloud, data, analytics, or GenAI tools) who want to understand how product decisions are made.