ELVTR: Product Management for AI & ML

ELVTR’s Product Management for AI & ML is a six-week live course taught by Swaroop Desai, a Lead Product Manager at Meta who has spent a decade leading AI product work, including AI transformation of Facebook Search. The course runs Mondays and Wednesdays in the evenings, with the next cohort running May 4 through June 17, 2026.

Who it is for

The course is aimed at practicing product managers who want to add AI and ML fluency to their existing skill set, junior AI/ML PMs who want to deepen their knowledge, and professionals transitioning into AI product roles from adjacent disciplines such as data science or business management. No prior AI experience is stated as a requirement.

What it covers

The curriculum spans thirteen modules that follow the arc of an AI product from conception to post-launch management. The first half covers foundations: the AI PM role, problem framing, how data works in AI systems, and core ML concepts explained at a PM-relevant level rather than an engineering depth. The second half addresses generative AI and prompt engineering, how to identify AI product opportunities, measuring business impact with KPIs appropriate for probabilistic systems, and responsible AI and governance. The course ends with execution and go-to-market strategy, AI team dynamics, future trends, and a capstone project — a portfolio-ready AI product pitch deck. A career guidance session is also included.

The instruction method combines live sessions, workshops, case studies, and prompt engineering exercises. Real-world examples include recommender systems and autonomous vehicles. Four graded assignments run throughout the course.

What it does not cover

The course does not go into production engineering or infrastructure — it is designed for PMs who need to work alongside AI teams, not for engineers building model pipelines. Pricing is not disclosed upfront; the site offers a $200 tuition credit for applicants, but the full fee requires contacting ELVTR directly, which adds friction compared to courses with transparent pricing.

Worth taking if

You are a practicing PM who has been working around AI features for a while but without a structured foundation, and you want a live instructor you can ask questions of rather than a self-paced curriculum. The Meta background of the instructor means the examples skew toward large-scale consumer AI, which is useful context even if your company operates at a different scale.