Overview
Define and manage AI products across the full lifecycle, from problem discovery to launch and continuous improvement, Identify AI-ready problems using problem-first thinking, feasibility checks, and business impact evaluation, Translate business goals into AI requirements and collaborate effectively with data science and engineering teams, Design human-centered, trustworthy AI experiences with transparency, oversight, and ethical safeguards, Measure AI product success using both business metrics and model performance indicators, Monitor AI systems in production, detect drift, and drive continuous improvement through feedback loops, Navigate ethics, governance, privacy, and regulatory requirements for real-world AI products, Build strategic leadership skills to communicate AI decisions clearly to executives and stakeholders
Product managers and product owners looking to transition into AI-driven products, Aspiring AI Product Managers seeking practical, real-world skills beyond theory, Founders and startup leaders building AI-powered products or features, Engineers and data professionals moving into product or decision-making roles, Business leaders responsible for AI initiatives and product strategy, UX, design, and research professionals working on AI-enabled user experiences
No prior AI or machine learning experience required; core concepts are explained from a product manager’s perspective, Basic understanding of product management or software products is helpful but not mandatory, Experience working with cross-functional teams (engineering, design, business) is beneficial, Comfort with structured thinking, writing short documents, and making decisions under uncertainty, Access to a laptop and stable internet connection for videos, labs, and assignments, Willingness to think critically, challenge assumptions, and engage with real-world case scenarios
“This course contains the use of artificial intelligence”
AI Product Management: Build What Actually Works is a deep, end-to-end program designed to help you build, launch, and scale AI products that deliver real business value—without losing sight of the human impact. This course goes beyond buzzwords, tools, and surface-level frameworks. It trains you to think like an AI Product Manager who can bridge strategy, technology, users, and execution in complex, uncertain environments.
Over 18 weeks and 90 structured learning days, you will develop a human-first, business-driven mindset for AI products. You will learn not just what AI can do, but when it should be used, when it should not, and how to ship it responsibly. The course is intentionally practical, combining clear conceptual lessons with hands-on labs, written assignments, and real-world decision frameworks used by experienced AI PMs.
You’ll start by building a strong foundation in AI Product Management fundamentals, understanding how AI products differ from traditional software products in lifecycle, risk, metrics, and failure modes. From there, you’ll gain essential AI literacy tailored specifically for product managers—covering AI vs ML vs GenAI, learning paradigms, LLMs, feasibility assessments, and limitations—without requiring you to become a data scientist.
As the course progresses, the focus shifts to users, problems, and data. You’ll learn how to identify AI-ready problems, design AI-specific personas, manage trust, evaluate data quality and bias, and treat data as a long-term product asset. You’ll then move into discovery, validation, and experimentation, learning how to define AI MVPs, design experiments, and implement human-in-the-loop systems.
A major emphasis of the program is metrics, evaluation, and continuous improvement. You’ll learn how to balance business outcomes with model performance, monitor drift, design feedback loops, and drive iterative improvement in production AI systems. Ethics, governance, privacy, explainability, and regulatory considerations are integrated throughout—so you can build products that are not only effective, but defensible and compliant.
In later stages, you’ll develop system-level thinking across architecture, UX for AI, execution, go-to-market, reliability, and operations. You’ll practice roadmap planning, stakeholder management, pricing, launch readiness, incident response, and vendor risk management—skills critical for real-world AI product leadership.
The final third of the course focuses on strategy, scaling, leadership, and career readiness. You’ll learn how AI creates competitive moats, how to scale responsibly, how to communicate with executives and boards, and how to position yourself as an AI Product Manager in the market. The course concludes with a full end-to-end synthesis, helping you create your own AI PM playbook and long-term growth plan.
By the end of this program, you won’t just understand AI products—you’ll know how to build what actually works, align AI with business reality, earn user trust, and lead AI initiatives with confidence and clarity.
Siam Hossain
Siam Hossain is an immigrant founder building across education, employment, and equity for migrants.
He first started HigherStudyAbroad, a 220,000-member nonprofit helping students from developing countries access top global universities.
He then founded Algorizin, a career accelerator that has helped 200+ immigrants land over $13M in high-paying tech jobs in the US.
Recently he launched XenosWealth, a wealth management platform focused on helping immigrants build generational wealth.