Indian Institute of Technology Kanpur

AI Integrated Product Management Program

Indian Institute of Technology Kanpur

Product Management

Application Deadline Approaching

Last date to apply: January 1, 2027 · Start date to be updated

About Programme

Master AI across the product lifecycle and build the skills needed for the next generation of product leadership.

Become an AI-enabled Product Manager. Master product strategy, analytics, growth, and AI across the full PM lifecycle.
Build products with proven PM frameworks and tools. Go hands-on with Figma, Jira, Mixpanel, ChatGPT, Claude, Cursor, Gemini, and NotebookLM.
Develop a portfolio-worthy capstone project. Apply AI and product management skills to take a product from research and strategy to UX, analytics, and GTM.
Built for working professionals. 4 months, weekend live classes, 60+ hours of learning.

What you'll learn

Use AI to Make Smarter Decisions Across the Product Lifecycle
Build Product Strategies, Roadmaps, and Priorities That Drive Business Impact
Identify Customer Needs and Validate High-Potential Product Opportunities
Leverage Analytics and Experimentation to Improve Product Outcomes
Create and Assess AI-Powered Features with Confidence and Responsibility
Demonstrate Your Skills Through Real-World Case Studies and a Capstone Project

Skills you'll gain

Product Strategy Product RoadmappingCustomer Discovery & User ResearchProduct Analytics & ExperimentationAI Product Management Agile Product Development PRD Writing & Product Documentation Data-Driven Decision Making

Programme Content

Foundations of Modern Product Management

Key Topics:

  • Evolution of Product Management and PM Roles
  • Product vs Project vs Program Management
  • B2B vs B2C Product Management
  • Product Lifecycle and Customer-Centric Thinking
  • Product Success Metrics and AI-driven Product Ecosystems
  • Product Teardown: Digital Product Case Studies
  • Learning Outcomes:

    Develop a strong foundation in modern product management, customer-centric product thinking, business models, and AI-enabled product ecosystems.

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    User Research, Customer Discovery & Problem Framing

    Key Topics:

  • User Research and Customer Discovery
  • User Personas, JTBD, and Customer Journey Mapping
  • Market Research and Competitor Benchmarking
  • Problem Prioritization Frameworks
  • AI-assisted Research Workflows
  • Product Teardown: For User Experience
  • Learning Outcomes:

    Learn to identify customer needs, validate opportunities, and frame high-impact product problems using structured and AI-assisted approaches.

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    Product Strategy & Roadmapping

    Key Topics:

  • Product Vision, Mission, and Strategy Frameworks
  • Product-Market Fit and Positioning
  • Roadmapping and Prioritization Techniques
  • North Star Metrics and Stakeholder Management
  • Business Models for Digital and AI Products
  • Case Study
  • Learning Outcomes:

    Build capabilities in product strategy formulation, roadmap creation, and aligning business objectives with customer and market needs.

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    Product Design, UX & AI Product Experiences

    Key Topics:

  • Design Thinking and UX Fundamentals
  • Wireframing and Prototyping
  • Conversational UX and AI-native Experiences
  • Personalization and Recommendation Systems
  • AI Trust, Feedback Loops, and Responsible Design
  • Product Teardown
  • Learning Outcomes:

    Understand how to design intuitive, trustworthy, and AI-powered product experiences that enhance customer engagement.

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    Agile Product Execution & Product Operations

    Key Topics:

  • Agile, Scrum, and Kanban Frameworks
  • Sprint Planning and Backlog Management
  • PRDs, User Stories, and Acceptance Criteria
  • Product Operations and Cross-functional Collaboration
  • AI-assisted Product Execution Workflows
  • Case Study: Agile Teams in SaaS Organizations
  • Learning Outcomes:

    Develop practical skills for managing product delivery, collaboration, and execution in modern agile environments.

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    Product Analytics & Experimentation

    Key Topics:

  • Product Metrics, Funnels, and Cohort Analysis
  • A/B Testing and Experimentation Frameworks
  • Event Tracking and Data-driven Decision Making
  • AI-assisted Analytics and Insight Generation
  • Product Teardown: LinkedIn and Instagram Growth Models
  • Product Management Tools
  • Learning Outcomes:

    Learn to leverage analytics and experimentation to measure product performance and drive strategic product decisions.

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    Generative AI for Product Managers

    Key Topics:

  • Generative AI and Large Language Models (LLMs)
  • Prompt Engineering for Product Workflows
  • AI-assisted Research, Documentation, and PRDs
  • Personalization Systems and AI Product Risks
  • Responsible AI and Ethics
  • Learning Outcomes:

    Build the ability to effectively integrate Generative AI tools into product management workflows while understanding their opportunities and limitations.

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    Advanced AI Product Systems & Enterprise AI Management

    Key Topics:

  • AI Product Architecture and RAG Systems
  • AI Agents, Evals, and Reliability Frameworks
  • Enterprise AI Product Management
  • AI Governance, Compliance, and Monetization Models
  • Context Engineering and Human-AI Collaboration
  • Case Study
  • Learning Outcomes:

    Develop advanced competencies in managing enterprise-grade AI products, architectures, and governance mechanisms.

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    Product Growth, Go-to-Market & Monetization

    Key Topics:

  • Go-to-Market Strategy and Product-led Growth
  • User Acquisition, Retention, and Engagement
  • Pricing and Monetization Models
  • SaaS Metrics and Growth Loops
  • Customer Success Fundamentals
  • Product Teardown
  • Learning Outcomes:

    Gain expertise in launching, scaling, and monetizing digital and AI-enabled products through data-driven growth strategies.

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    Industry Applications & AI Product Case Studies

    Key Topics:

  • AI Applications in SaaS, FinTech, Healthcare, and E-commerce
  • Enterprise AI Transformation and Automation Platforms
  • Emerging AI Product Trends
  • Industry Case Studies
  • AI Product Opportunity Identification Workshop
  • Learning Outcomes:

    Understand real-world AI product implementations and identify future opportunities across multiple industry sectors.

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    Capstone Project: AI-Integrated Product Strategy Development

    Key Components:

  • User and Market Research
  • Product Vision, Strategy, and Roadmap Development
  • AI Feature Identification and Integration
  • PRD, Wireframes, and User Experience Flows
  • Product Analytics Framework
  • Go-to-Market and Monetization Strategy
  • Final Product Pitch and Executive Presentation
  • Learning Outcomes:

    Develop a comprehensive, industry-relevant AI product portfolio project that demonstrates end-to-end product management capabilities and can be showcased in resumes, LinkedIn profiles, and product management interviews to strengthen career opportunities.

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    Career Advancement Workshop

  • Product Management Career Pathways
  • Portfolio Building and Resume Optimization
  • AI-assisted Personal Branding
  • Product, Strategy, and Analytics Interview Preparation
  • Personal Project Reviews and Expert Feedback
  • Outcomes:

    Strengthen career readiness through portfolio development, interview preparation, and personalized guidance for product management roles.

    Download Full Curriculum

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    Indian Institute of Technology Kanpur

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    https://www.iitk.ac.in
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    AI Integrated Product Management Program | IIT Kanpur