AI Product Management Program

AI Product Management is a live, instructor-led program designed to build strong skills in designing, launching, and managing AI-driven products using modern product strategy, data insights, and AI technologies.

  • This 24-week structured journey includes real product development case studies, 10+ hands-on workshops, 30+ real-world AI product use cases, and masterclasses with continuous mentorship.
  • You will work with product analytics platforms, AI product frameworks, user research methods, and AI technology stacks to build portfolio-ready product strategy outputs.
  • The program also provides an option to pursue industry-recognized certifications including Google Product Management Certificate, Microsoft AI Product Manager credentials, CSPO, and Product School certifications.
Format Live Instructor-Led
Duration 24 Weeks | 180 Hours
Admission Deadline 30 April 2026
Case Studies & Projects 30+
Enroll Now

Key Program Takeaways

Build real AI product management capability through guided product strategy labs, AI product workflows, and project-based learning designed for launching and scaling AI-driven products.

AI Product Strategy

AI Product Vision, Market Opportunity, Product Roadmaps

User Research & Product Discovery

Customer Insights, Problem Definition, Product Requirements

AI Technology Understanding

AI Capabilities, LLM Applications, Data-Driven Product Design

Product Analytics

Metrics, Experimentation, Data-Informed Decisions

Product Development & Launch

Agile Product Development, MVP Design, Go-to-Market Strategy

Capstone Portfolio

End-to-End AI Product Strategy & Launch Plan

List of Modules in this Program

01

Foundations of AI Product Management

  • Introduction to AI-driven products and the AI product lifecycle.
  • Understand how AI capabilities translate into real product opportunities.
  • Overview of AI product ecosystems and successful AI product case studies.
02

Product Discovery & User Research

  • Identify market opportunities and customer problems.
  • Conduct user research and define product requirements.
  • Develop product vision, value propositions, and roadmaps.
03

AI Technologies for Product Managers

  • Understand machine learning, generative AI, and LLM capabilities.
  • Learn how AI models, datasets, and infrastructure power AI products.
  • Evaluate feasibility, risks, and ethical considerations in AI systems.
04

Product Analytics & Data-Driven Decisions

  • Define product metrics and success indicators.
  • Analyze user behavior and product performance using analytics.
  • Run experimentation and A/B testing for product improvement.
05

Product Development & Go-to-Market Strategy

  • Work with engineering teams using Agile development frameworks.
  • Design MVPs, prioritize features, and manage roadmaps.
  • Plan launches, growth strategies, and product scaling.
06

Capstone Project

  • Design and develop a complete AI product strategy.
  • Define product vision, technical architecture, and market positioning.
  • Present a portfolio-ready roadmap and go-to-market plan.

Hands-On Roadmap

Weeks 1–4

AI Product Foundations & Market Understanding

  • Explore AI product landscapes and emerging use cases
  • Learn AI capabilities, limitations, and product potential
  • Conduct market research and competitive analysis
  • Hands-on: AI Product Opportunity Map, Market Analysis Report
Weeks 5–8

Product Discovery & User Research

  • Conduct user research and stakeholder interviews
  • Define user personas and product requirements
  • Create product vision and value propositions
  • Hands-on: User Persona Framework, AI Product Requirements Document
Weeks 9–12

AI Product Design & MVP Development

  • Translate AI capabilities into product features
  • Define MVP scope and feature prioritization
  • Collaborate with engineering teams on product design
  • Hands-on: AI Product Feature Roadmap, MVP Design Blueprint
Weeks 13–16

Product Analytics & Experimentation

  • Define product metrics and key performance indicators
  • Analyze usage data and user behavior
  • Run experiments and A/B tests to validate product decisions
  • Hands-on: Product Metrics Dashboard, Experimentation Framework
Weeks 17–20

Product Launch & Growth Strategy

  • Develop go-to-market strategies for AI products
  • Define pricing models and growth strategies
  • Manage cross-functional product development workflows
  • Hands-on: AI Product Go-to-Market Plan, Growth Strategy Framework
Weeks 21–24

Capstone AI Product Project

Design and present a complete AI product strategy.
  • Define product vision, roadmap, and technical architecture
  • Create launch strategy and product growth plan
  • Present a comprehensive AI product case study
  • Capstone project options:
  • AI-Powered Customer Support Product
  • Intelligent Business Analytics Platform
  • AI Productivity Assistant Product Strategy

Top Companies Hiring AI Product Managers

Leading technology companies, AI startups, consulting firms, and digital platforms actively hire professionals to lead strategy, development, and launch of AI-powered products.

Google Microsoft Amazon Meta Apple OpenAI NVIDIA Tesla IBM Oracle Salesforce McKinsey & Company BCG Bain & Company Deloitte Accenture Goldman Sachs JPMorgan Chase Morgan Stanley Flipkart Paytm Razorpay Swiggy Zomato PhonePe Infosys TCS Wipro Cognizant

Some of our exceptional outcomes with top companies.

Sai Arya

Sai Arya

₹65 LPA CTC

Nitish

Nitish

₹65 LPA CTC

Manurbhav A

Manurbhav A

₹21 LPA CTC

Aditya T

Aditya T

₹21 LPA CTC

Om Nakrani

Om Nakrani

₹65 LPA CTC

Yuvana T

Yuvana T

₹22 LPA CTC

Pardhiv A

Pardhiv A

₹21 LPA CTC

Phanindra B

Phanindra B

₹19 LPA CTC

Sai Gokul

Sai Gokul

₹65 LPA CTC

Abhigyan N

Abhigyan N

₹65 LPA CTC

Aryan T

Aryan T

₹21 LPA CTC

Devendra A

Devendra A

₹65 LPA CTC

Mahesh Reddy

Mahesh Reddy

₹65 LPA CTC

Prakul K

Prakul K

₹21 LPA CTC

Prashanth Reddy K

Prashanth K

₹65 LPA CTC

Rajeev T

Rajeev T

₹21 LPA CTC

Master Technologies

Core AI product, analytics, experimentation, and product management tools used throughout the program.

Product Analytics Tools (Mixpanel / Amplitude)
SQL logoSQL
Python logoPython (for Product Analytics)
Excel / Google Sheets
A/B Testing Frameworks
Product Experimentation Tools
AI APIs (OpenAI / Google AI / Azure AI)
Prompt Engineering Tools
Data Visualization Tools (Tableau / Power BI)
Product Roadmapping Tools (Productboard / Aha!)
Agile & Scrum Frameworks
Jira logoJira
Confluence logoConfluence
Notion logoNotion
Figma logoFigma
Miro logoMiro

Eligibility & Admission

A fully online, straightforward admissions process with advisor support throughout enrollment.

Who Can Apply Eligibility requirements for enrollment
  • Graduates in engineering, management, commerce, economics, IT, or related disciplines.
  • Final-year undergraduate students completing their degree before the program concludes.
  • Working professionals in product, strategy, consulting, analytics, and technology roles looking to transition into AI product leadership.
Admission Process Simple, structured steps from application to enrollment
  1. Application Submission: Complete a short online application with academic/professional details.
  2. Profile Review: Selected applicants receive official admission confirmation.
  3. Seat Confirmation: Reserve your seat with INR 10,000.
  4. Fee Completion: Pay the remaining fee within 7 days of confirmation or before program start, whichever is earlier.
Learner Assistance Advisor support throughout your admission journey

Program advisors are available 7 days a week, 10:00 AM to 7:00 PM.

Email: hello@42learn.com

Phone: 080 4736 3406

Disclaimer: Outcome, career progression, and salary information is indicative only; individual results vary by background, experience, and market conditions. Certificates/credits are governed by the issuing institution's policies where external partners are involved.