AI 4 PMs
Learn how to build AI based products in 7 weeks from industry’s top experts while contributing society
A program designed for experienced Product Managers who are excited to level up as AI Product Managers
About the course
AI4PM is a practical, modern course designed for experienced product managers who want to confidently lead AI products from concept to execution. This isn’t a theoretical lecture series; it’s an immersive program where you’ll bridge the gap between AI capabilities and real-world product strategy.
Throughout the course, you’ll get hands-on experience working with AI building blocks and collaborating on real-world use cases. You’ll step into the shoes of an AI PM, learning how machine learning, generative AI, and AI agents function in practice, how to map data requirements, and how to design responsible, user-centered AI experiences.
The Hands-On Experience
We believe in learning by doing. During the course, you will:
- Build & Prototype: Get your hands dirty interacting directly with LLMs and AI tools to explore capabilities and workflows. (cursor, Claude Code)
- Analyze Real-World Case Studies: Dissect actual deployment challenges, product failures, and successes from top-tier tech companies.
- Collaborate on AI Use Cases: Work alongside peer PMs to solve complex product dilemmas and simulate real AI team dynamics.
Most importantly, you’ll master the day-to-day tools, workflows, and communication strategies needed to collaborate effectively with data scientists and engineers.
What will you learn?
Machine learning basics
- Data science principles
- Supervised and unsupervised learning
- Model evaluation metrics
- NLP
- Generative AI
- LLMs
- Product management practices in the AI field
- Ethical dilemmas leading AI products
- Career path as AI Product Manager
Course Takeaways
By the end of this program, you won’t just know the AI terminology.
You’ll have the practical frameworks, mental models, and hands-on confidence to instantly elevate your capabilities and lead AI initiatives within your organization.
Things you should know
Starting on June 3 to July 15, the program will last for 7 weeks, every Wednesday evening between 19:00-21:00.
It is an online zoom based program, except for 3 meetups, the first and the last and one during the course that will be held F2F.
The program will be held in Hebrew.
80% of the proceeds are donated to nonprofit organizations
The other 20% helps us expand our activity
Got Questions? We've Got Answers
Starting on June 3 to July 15, the program will last for 7 weeks, every Wednesday evening between 19:00-21:00.
Product managers with at least 2 years of practical experience or equivalent.
Familiarity with basic statistics is required.
Recommended to have a technical background.
Initial application
Please note this doesn’t guarantee your place in the course, as we need to make sure applicants meet our minimum requirements for the course (you can see them under ‘Course Requirements’).
Registration ends on 27.05.26.
Donate and secure your place
Once you receive an email from us, you will have 48 hours to complete the registration and secure your spot in the course. The ‘cost’ of the course is a donation of minimal 2200₪. You will be able to choose how much you’d like to donate.
- Participate in at least 80% of the lectures and practice sessions
- 7 weeks, 2 hours sessions will help you get all the background required to kick start as an AI PM.
- Course fee – donation
- Coursedonation starting at 2200 nis and you can donate higher if you wish
The association’s approach is that the donation is not a payment for the course (it is a donation and the course is a by-product), so there is no direct relationship between the number of sessions the student has had and one refund or another.
If we think the course is not for you after one or two meetings – we will return the full amount and check if it is possible to put someone else in your place.
Participants are being selected based on their professional background and their potential to benefit from the program’s content.
All course lectures, practice sessions and panels will be held in Hebrew only.
Most sessions will be recorded subject to approval by the lecturers. It is recommended to verify with the course staff beforehand.
Coursedonation starting at 2,200 nis and you can donate higher if you wish
Registration ends on 27.05.26
Course Staff
Rita Kagan
Product Management | AI/Gen-AI ✨
Tal Elor
Co-Founder & CTO @ Athena | AI Product Management
Or Hay
Senior AI Product Manager @ monday.com
Yaron Helfer
Product Team Lead @ LSports
Carolina Fain
Product Manager
Shani Dotan
Product Management Leader
Sagi Angel
Product Manager @ CathWorks
Our Lecturers
Hilly Noy
Director of Product Management @ SysAid
Itay Kaplan
Director of Product Management GenAI @ WSC Sports
Adi Livne
Product Designer at monday AI
Shai Passal
Senior User Experience Researcher @monday.com
Hadar Weinberger
AI Product Leader | Co-Founder @ Product For Product
Tal Elor
Co-Founder & CTO @ Athena | AI Product Management
Rita Kagan
Product Management | AI/Gen-AI ✨
Roy Leiser
Product Manager @ Meta
Or Hay
Senior AI Product Manager @ monday.com
David Columbus
AI Architect @ Siemens DI SW
Tomer Simon
Principal AI Product Manager @ AIDOC
Keren Katz
Senior Group Manager – Product, Threat Research and AI @ Tenable
Elena Levi
Director of Product @ Payoneer
Shelly Shmurack
Data PM | Product Management Podcaster, Speaker & Mentor
Course Syllabus
In the course of 7 sessions, we’ll review the basics concepts of machine learning, and how they interact with the world of product management. We will discuss product management processes and methodologies and how we can use them to build ML products.
Course intro, AI PM role, and CRISP-DM framework
Gen AI
Supervised/unsupervised learning, deep learning, Key metrics and evaluation techniques for ML models
Understanding what LLMs are, how they work, and common applications
Perhaps followed by Prompt engineering
- what AI evals are there? What to choose? How to assess your LLM application?
- What are AI agents? How they function and product opportunities around them
GenAI tools + practice group time about the previous lessons (AI competition?)
- UX&UI guidelines for AI based products, what is the difference comparing to usual user experience definition
- Explore how AI product strategies are built and executed in real organizations, based on Roy’s experience at Meta, Amazon, and startups.
Share few examples of end to end success AI Product stories -Final session
