AI Product Management Courses Compared with Employer Demand: Syllabus Coverage and Price of Leading Programs against 1,082 Job Postings

Courses that promise to turn product managers (PMs) into AI product managers have multiplied, but there is little public evidence on whether what they teach matches what employers ask for. This paper compares the public syllabi of 29 AI product management courses with the content of 1,082 PM job postings at 165 companies (the AllthingsPM PM Hiring Index), harvested on 9 November 2026 from the public Greenhouse, Ashby and Lever job-board APIs. I define 13 AI PM themes, measure each theme's share of the 496 AI-focused postings with published keyword rules, and code every course's syllabus page on each theme (0 absent, 1 mentioned or one unit, 2 substantial), with the evidence phrase for every cell released. Employers most often mention LLM fundamentals (71.0% of AI-focused postings), enterprise deployment and integration (70.0%) and agents (68.5%); prompting (14.3%) and fine-tuning or retrieval (16.7%) are among the least mentioned. Courses cover strategy and LLM basics almost universally, but only 14 of 28 external courses mention enterprise deployment and 10 mention multimodal products. A demand-weighted alignment score (0 to 100) has a median of 47.5 for external courses. The AllthingsPM course, built by the author, scores highest (98.7; 92.4 under a stricter chapter-level coding), followed by the IIT Kharagpur executive certificate (88.7) and Mahesh Yadav's Agentic AI PM certification (75.1). Prices used for the analysis run from free to USD 9,550, with a median of about USD 1,600 for priced external courses; a Packt course on Coursera (about USD 59) and AllthingsPM (USD 108 a year) cost the least per alignment point. On a composite of alignment (50%), value (25%) and 13 design parameters (25%), AllthingsPM ranks first, and it stays first under alignment-only, equal and value-first weightings. Under a weighting for learners who want live teaching and a recognised certificate it ranks 16th, and IIT Kharagpur ranks first. The author's conflict of interest, the author-chosen design parameters and single-coder coding are the main limitations; the coding table is released for independent re-coding. Files: the paper (PDF) and the course coding data (coverage-coding.csv with an evidence phrase and URL per cell, design-parameters.csv, courses-summary.csv, scripts). Data: AllthingsPM PM Hiring Index, November 2026, doi:10.5281/zenodo.24072616. Part of the AllthingsPM PM Hiring Index working paper series. Author: Arpit Ranjan, AllthingsPM (allthingspm.app). Conflict of interest: the author is the founder of AllthingsPM and built one of the compared courses.