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Pravartak

Professional Advanced Certification in Product Management with AI

5 4327 Ratings
  • Gain expertise in product lifecycle management, market analysis, agile methodologies, and user experience design.
  • Master the latest tools and techniques with hands-on projects and real-world case studies.
  • Learn product management from IIT faculty & industry experts.
  • Get Advanced Certification in Product Management with AI from IITM Pravartak.
  • Master generative and agentic AI use cases in product management.
Applications closes on 22nd Nov 2025
IITM Research

9 Months Program

Learning Format

Online

Certification

IITM Pravartak

Career Boost

Resume & Interview Prep

With Job Assistance

Best For

Graduates and Working Professionals

Looking to Switch to Product

Our Proven Track Record

Our consistent track record of success shows clearly our dedication to excellence.
Successfull Job Placement
₹45 LPA Highest CTC Secured by Learners

Our learners have successfully transitioned into high-growth product roles, securing up to ₹45 LPA, regardless of their previous background.

55% Average Salary Hike After Completion

Over half of our learners reported a significant salary boost post-program, accelerating their transition into core product management roles.

95% Learner Satisfaction Score

From IIT-certified curriculum to dedicated career support, 95% of learners expressed high satisfaction with the program.

Real Stories, Incredible Journeys

Swipe to find learners like you, or speak to a career expert and get started today.

3100+ Companies Hired Our Intellipaat Learners

Intellipaat students have left a remarkable imprint in the growing IT sector, garnering acknowledgement from CXOs, and HR leaders across top tech companies. Listen indirectly from them.
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Why Leading Companies Trust Intellipaat Students: HR Perspectives

Leading companies acknowledge the expertise of Intellipaat students. Hear firsthand from top executives and hiring professionals.
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World Class Instructors

Learn from India's best IIT faculties and Top 1% Industry Experts!
World Class Instructors
Group 2708
Technical Instructors
  • Gain product management expertise from IIT faculty and elite industry professionals.
  • Work on real-world projects and receive hands-on guidance from Subject Matter Experts (SMEs).
Group 2845
Learning & Support Mentors
  • A dedicated Learning Mentor to guide you through your journey and ensure consistent progress.
  • Track performance, clarify doubts instantly, and receive personalized support throughout the course.
Group 2846
Placement Mentors
  • Live training sessions to enhance communication, product thinking, and resume presentation.
  • Crack interviews with confidence using proven frameworks from top product hiring experts.
Hear directly from our learners as they recount their journeys with Intellipaat
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Intellipaat vs Others

Fees
World-Class Instructors
Advanced Curriculum
Capstone Projects
Job Assistance
Intellipaat
₹1,35,000
Learn from IIT faculty and top 1% product leaders
Future-proof syllabus including Gen AI, Agile, UX & Strategy
50+ industry-grade real-world projects and case studies
1:1 mock interviews, resume reviews, career support via Intellipaat Portal
Others
₹3,00,000 – ₹4,00,000
Limited exposure to experienced professionals
Outdated, generic product content
Focus on theory with minimal real-world exposure
No structured placement support

Curriculum

1
Introduction Phase
Prerequisite Sessions

Managing Product Development Methodology

  • Fundamentals of Agile and Lean Development

Microsoft Excel

  • Excel Fundamentals
  • Excel For Data Analytics
  • Data Visualization with Excel

Project Management Tools – JIRA Software for Beginners

  • Product introduction
  • Installation and System Requirements
  • Applications, Uses, and Examples
  • JIRA core concepts
  • Project Setup
    • Create project categories
    • Create project
    • Project configuration walkthrough
    • Components and versions
  • JIRA Interface Walkthrough

Dashboards

  • Creating, Sharing and Configuring Dashboards
  • Adding Gadgets to Dashboards and Configuring Them
  • Creating, Sharing, and Configuring Filters
  • Subscriptions
  • Searching in Jira (Issue Navigator, Basic Search, and Advanced Search)
  • JQL (Theory and Sample JQLs)

UML 2.0

  • Class diagram
  • Component diagram
  • Composite structure diagram
  • Deployment diagram
  • Object diagram
  • Package diagram
  • Profile diagram
  • Activity diagram
  • State machine diagram
  • Use case diagram
  • Communication diagram
  • Interaction overview diagram
  • Sequence diagram
  • Timing diagram
Project Management Tools - JIRA Software for Beginners
  • Product introduction
  • Installation and System Requirements
  • Applications, Uses, and Examples
  • JIRA core concepts
  • Project Setup
    • Create project categories
    • Create project
    • Project configuration walkthrough
    • Components and versions
  • JIRA Interface Walkthrough

Dashboards

  • Creating, Sharing and Configuring Dashboards
  • Adding Gadgets to Dashboards and Configuring Them
  • Creating, Sharing, and Configuring Filters
  • Subscriptions
  • Searching in Jira (Issue Navigator, Basic Search, and Advanced Search)
  • JQL (Theory and Sample JQLs)
Wireframing and Prototyping Tools: Figma, Sketch
  • Working With the Design Process and Thinking Method
  • Experiencing the Design Process Tools
  • Examine the Usability Evaluation
How to Use GenAI & Digital Tools
  • Using ChatGPT/Google Forms
Managing Product Development Methodology
  • Fundamentals of Agile and Lean Development
Analytics Tool
  • Google Analytics
2
Phase 1: Product Management Fundamentals & AI Product Lifecycle Management
Introduction to Product Management
  • What is Product Management?
  • Evolution of Product Management Roles
  • Key Skills and Responsibilities
  • Product Management vs. Project Management
  • Product Manager’s Role in Cross-functional Teams
  • Tools for Product Managers: Trello, Asana
  • Case Study: How Product Managers Drive Growth in Tech Startups
  • Best Practices for Product Management
Product Lifecycle and Strategy
  • Understanding Product Lifecycle Stages
  • Stages of Product Development: Introduction, Growth, Maturity, Decline
  • Product Strategy Development
  • Product Portfolio Management
  • Product Lifecycle Management Tools: Aha!, Jira
  • Case Study: Netflix’s Product Strategy Evolution
  • Evaluating Product Performance and Metrics
  • Strategic Decisions at Different Lifecycle Stages
  • Identifying Business Problems Suitable for AI
  • Translating Business Goals into AI Product Requirements
  • Scoping and Feasibility (Data, Infrastructure, Cost, Risk)
  • Managing Data and Model Lifecycles: Versioning, Testing, Validation
  • Designing Success Metrics for AI Products (Precision, Recall, Accuracy vs. Business ROI)
  • Deployment Strategies for AI Systems (Batch, Real-time, Edge, Serverless)
  • Monitoring and Governance: Detecting Model Drift, Data Drift, and Bias
  • Continuous Learning and Product Evolution
3
Phase 2: AI Product Strategy and Value Proposition
AI Product Strategy and Stakeholder Alignment
  • Translating high-level business goals into an actionable AI product strategy that drives measurable business outcomes.
  • Prioritizing AI use cases and managing feature backlogs with clarity, alignment, and strategic focus.
  • Communicating the value of AI initiatives effectively to leadership and cross-functional teams to ensure adoption and accelerate execution.
Product Features and Product Lines
  • Understanding Product Features
  • Product Mix and Product Lines
  • Designing Product Features and Specifications
  • Product Line Extensions and Modifications
  • Product Portfolio Management Tools – Overview
  • Case Study: Apple’s Product Line Strategy
  • Evaluating Product Features for Customer Fit
  • Strategic Decisions on Product Lines
Value Creation, Communication, and Delivery
  • Value Creation: Understanding Customer Needs
  • Value Communication Strategies
  • Co-creation with Customers
  • Value Delivery: Traditional vs. Contemporary Models
  • Porter’s Value Chain Analysis
  • Case Study: Porter’s Value Chain: Indraprastha Ice & Cold Storage
  • Measuring Value Delivery Effectiveness
  • Improving Value Delivery Processes
4
Phase 3: Competitive Strategies and Innovation
Strategic Approaches for Competitive Advantage
  • What is Strategy? Definitions and Misconceptions
  • Porter’s Generic Strategies: Cost Leadership, Differentiation, Focus
  • Developing Competitive Strategies
  • Core Competency Analysis
  • SWOT Analysis: Strengths, Weaknesses, Opportunities, Threats
  • Strategic Business Units (SBUs) and Their Relevance
  • Tools: SWOT Analysis Template (Excel, Power BI)
  • Case Study: Disney & UTV Strategic Alliance
  • Strategic Planning, Implementation, and Control
Disruptive Innovation and Product Strategy
  • What is Disruptive Innovation?
  • Disruptive Innovation Models and Theories
  • Ansoff’s Product Market Expansion Grid
  • Market Opportunity Analysis for Innovative Products
  • Growth Strategies and Strategic Planning Gaps
  • Tools: Ansoff Grid, Innovation Management Software
  • Case Study: ideaForge’s Disruptive Innovation in Drones
  • Managing Status Quo in Disruptive Innovation
  • Evaluating Impact of Disruptive Innovations
5
Phase 4: Product Development and Market Orientation
New Product Development (NPD) Process
  • Overview of the NPD Process
  • Identifying Customer Needs and Market Research
  • Product Planning and Feature Definition
  • Concept Generation, Screening, and Testing
  • Tools: MindMeister, Conceptboard
  • Case Study: Tesla’s Product Development Strategy
  • Product Launch Strategies
  • Measuring NPD Success and Iteration
Jobs-to-be-Done (JTBD) Framework
  • Understanding the Jobs-to-be-Done (JTBD) framework and its application in identifying real user needs and motivations.
  • Crafting AI product features around “jobs” customers are trying to accomplish rather than demographics or personas.
  • Conducting user interviews and translating JTBD insights into actionable AI product requirements and innovations.
Minimum Viable Product (MVP) & Minimum Delightful Product (MDP)
  • Definitions and Differences Between MVP and MDP
  • Benefits of MVP and MDP Approaches
  • Designing MVP and MDP
  • Tools: Leanstack, Figma for Prototyping
  • Case Study: Dropbox MVP Success Story
  • Gathering Feedback and Iterating on MVP
  • Transitioning from MVP to MDP
  • Measuring MVP and MDP Success
Market and Competitor Orientation
  • Market Segmentation and Target Market Selection
  • Developing Buyer Personas, Tools: Make My Persona
  • Product Positioning and Messaging
  • Competitor Analysis and Market Positioning
  • Tools: SPSS for Competitor Analysis
  • Case Study: Switz Food’s Competitor Strategy
  • Adapting Product Strategy Based on Market Insights
  • Monitoring and Adjusting to Competitor Moves
6
Phase 5: Product Launch and Go-to-Market (GTM) Strategies
Go-to-Market (GTM) Strategy
  • Components of a GTM Strategy
  • Steps to Develop and Execute a GTM Plan
  • Product Launch Management
  • Tools: Airtable for GTM Planning
  • Case Study: Slack’s GTM Strategy
  • Best Practices for a Successful Product Launch
  • Managing Post-Launch Activities
  • Measuring GTM Effectiveness
  • Identifying target users, value propositions, and positioning strategies for successful AI product launches.
  • Coordinating launch activities across marketing, sales, and product teams to achieve measurable adoption and impact.
Sales Strategies and Managing Sales Force
  • Sales Strategy Development
  • Types of Sales Strategies: Direct, Channel, Indirect
  • Managing Sales Force and Compensation Models
  • Tools: Salesforce for CRM and Sales Management
  • Case Study: HubSpot’s Sales Strategy
  • Sales Force Training and Motivation
  • Analyzing Sales Performance Metrics
  • Aligning Sales and Product Management
7
Phase 6: Branding, Positioning, and Communication
Product Positioning and Brand Management
  • Key Elements of Product Positioning
  • Developing Brand Identity and Brand Equity
  • Creating Brand Positioning Statements
  • Understanding Branding Basics
  • Comparing Marketing, Advertising, and Branding
  • Analyzing Successful Brands and Their Characteristics
  • Exploring Consumer Marketing, Psychology, and Buying Behavior
  • Evaluating Brand Architecture and Portfolio Management
  • Developing Brand Planning and Strategy
  • Assessing the Evolution and Current Status of Ad Agencies
  • Applying Brand Management Strategies
  • Measuring and Evaluating Brand Performance
  • Designing Rebranding Strategies and Brand Evolution
  • Tools: Perceptual Mapping in Excel
  • Case Study: Launch of Pleasure Scooter
Marketing Communication for Product Success
  • Integrated Marketing Communication (IMC) Strategies
  • Effective Advertising Techniques
  • Communication Models and Platforms
  • Tools: Google Ads, Social Media Analytics
  • Case Study: Burger King’s Mouldy Burger Ad Campaign
  • Role of Value Networks and Channels
  • Managing Marketing Communications
  • Measuring Communication Effectiveness
8
Phase 7: Pricing Strategies
Pricing of Products
  • Principles of Pricing Strategy
  • Pricing Models and Strategies: Cost-Based, Value-Based, Competition-Based
  • Behavioral Pricing and Psychological Pricing
  • Tools: Pricing Model Templates in Excel
  • Case Study: Amazon’s Dynamic Pricing Strategy
  • Participative Pricing and Reference Pricing
  • Price and Non-Price Competition
  • Responding to Competitive Price Changes
9
Phase 8: Metrics and Goals in Product Analytics
Introduction to Product Analytics
  • Fundamentals of Product Analytics
  • Key Metrics and KPIs in Product Analytics
  • Tools: Mixpanel, Google Analytics
  • Case Study: Airbnb’s Data-Driven Product Decisions
  • Role of Data in Product Decision Making
  • Characteristics of High-Quality Analytics
  • Solving Product Management Problems with Analytics
  • Setting Analytics Objectives and Hypotheses
  • Defining clear success metrics and KPIs aligned with product and business objectives.
  • Using product analytics to measure user engagement, retention, and conversion across the AI product lifecycle.
  • Setting data-driven goals to evaluate the impact of AI features and guide continuous product improvement.
Product Analytics Process and Design
  • Stages of the Product Analytics Process
  • Designing Analytics for Product Management
  • Exploratory, Descriptive, and Causal Analytics
  • Case Study: Using Analytics for Product Optimization
  • Direct and Indirect Exploratory Methods
  • Role of Observation Methods in Product Management
  • Creating Effective Analytics Reports
Product Analytics Metrics and Goals
  • Measurement and Scaling Techniques
  • Discrete vs. Continuous Measurement Scales
  • Reliability and Validity of Measurement Scales
  • Tools: SurveyMonkey, Typeform for Data Collection
  • Case Study: Survey Analysis for Product Insights
  • Designing and Piloting Questionnaires
  • Evaluating and Interpreting Data
  • Setting and Tracking Analytics Goals
10
Phase 9: Advanced Data Analytics for Product Development
Data Cleaning, Coding, and Entry
  • Data Preparation Techniques
  • Handling Missing Values and Imputation
  • Data Coding and Entry Best Practices
  • Case Study: Chic-Chicken Hypothesis Testing
  • Organizing Data for Analysis
  • Secondary Data Analytics Techniques
  • Survey Data Analysis
Predictive & Descriptive Analytics in Product Management
  • Introduction to Descriptive Analytics
  • Importance of Descriptive Statistics in Product Management
  • What is Correlation Analysis
  • Hypothesis Testing and Types of Errors in Testing
  • Testing Approach: The P-Value/Significance Method
  • Introduction to Predictive Analytics
  • Difference Between Descriptive and Predictive Analysis
  • Regression Models and Predictive Indicators
  • Creating and Testing Predictive Models
  • Tools: SPSS, Excel for Regression Analysis
  • Case Study: Predicting Product Success with Regression
  • Multiple Regression Analysis
  • Dummy Variable Regression
  • Evaluating Model Accuracy and Assumptions
11
Phase 10: Consumer Behavior Analysis
Consumer Behavior Analytics
  • Importance of Analyzing Consumer Behavior
  • Factors Affecting Consumer Behavior
  • Using Factor Analysis for Customer Research
  • Tools: SPSS for Factor and Cluster Analysis
  • Case Study: Understanding Consumer Segments with Data
  • Principle Component Analysis and Factor Rotation
  • Cluster Analysis for Customer Segmentation
  • Analyzing and Interpreting Customer Preferences
Digital Analytics for Product Management
  • Introduction to Digital Analytics
  • Web Analytics and User Behavior Tracking
  • Conducting A/B Testing and Experiments
  • Tools: Google Analytics, Optimizely
  • Case Study: A/B Testing for Optimal User Engagement
  • Implementing and Analyzing Basket Analysis
  • User Journey Analysis and Funnel Analysis
  • Leveraging Digital Data for Product Improvements
12
Phase 11: Agile and Lean Development
Agile Development Methodologies
  • Agile Development Overview
  • Scrum Framework: Roles, Artifacts, Events
  • Kanban Method: Principles and Practices
  • Tools: Jira, Trello for Agile Project Management
  • Case Study: Microsoft’s Agile Practices
  • Agile Metrics: Velocity, Burndown Charts
  • Implementing Agile in Different Environments
  • Challenges and Solutions in Agile Development
Lean Development
  • Principles of Lean Thinking
  • Lean Startup Methodology: Build-Measure-Learn
  • Metrics and Continuous Improvement
  • Tools: KanbanFlow, LeanKit
  • Case Study: Lean at Toyota: Revolutionizing Product Development
  • Value Stream Mapping
  • Identifying and Eliminating Waste
  • Scaling Lean Practices Across Teams
13
Phase 12: Product Ideation, Design Thinking and Product Prototyping
Design Thinking Process
  • Stages of Design Thinking: Empathize, Define, Ideate, Prototype, Test
  • Techniques for Each Stage
  • Tools: Figma for Prototyping
  • Case Study: IdeaForge – Mechanical Charger
  • Empathy Mapping and User Research
  • Ideation Techniques and Brainstorming
  • Creating and Testing Prototypes
  • Iterative Design and Feedback Loops
Innovative Communication in Design Thinking
  • Effective Storytelling in Design Thinking
  • Communication Strategies for Innovation
  • Tools for Creative Communication: Miro, MURAL
  • Case Study: SoaPen’s Innovation Communication
  • Facilitating Workshops and Idea Sessions
  • Presenting Ideas to Stakeholders
  • Handling Feedback and Revising Prototypes
  • Best Practices for Communicating Design Innovations
Product Prototyping
  • What is Product Prototyping?
  • Need for Prototyping
  • Types of Prototypes: Low-Fidelity, Mid-Fidelity, High-Fidelity
  • Prototyping Tools and Techniques
  • Tools: Balsamiq, Figma for Prototyping
  • Case Study: Prototyping at Google Ventures
  • Rapid Prototyping Techniques
  • User Testing and Iteration
  • Prototyping for Different Stages of Product Development
  • Evaluating and Refining Prototypes Based on User Feedback
14
Phase 13: Product Roadmaps and Prioritization
Product Roadmapping and Prioritization
  • Elements of a Product Roadmap
  • Roadmap Planning and Prioritization Techniques
  • Tools: Aha!, Roadmunk
  • Case Study: Product Roadmaps in Spotify
  • Roadmap Communication and Stakeholder Management
  • Managing Roadmap Changes and Updates
  • Aligning Roadmap with Strategic Goals
  • Best Practices for Effective Roadmapping
15
Phase 14: Product Leadership and Team Building
Leadership in Product Development
  • Leadership Qualities for Product Managers
  • Building and Leading Cross-Functional Teams
  • Conflict Resolution and Team Dynamics
  • Tools for Leadership and Team Management
  • Case Study: Leading Product Teams at Atlassian
  • Motivating and Mentoring Team Members
  • Setting Team Goals and Objectives
  • Performance Management and Feedback
16
Phase 15: Specialized Topics and Trends in Product Management
Ethical Product Management
  • Ethical Considerations in Product Development
  • Navigating Ethical Challenges and Dilemmas
  • Tools for Ethical Decision Making
  • Case Study: Facebook and the Cambridge Analytica Scandal
  • Building Ethical Guidelines and Frameworks
  • Managing Public Relations and Ethical Issues
  • Legal and Regulatory Compliance
  • Promoting Ethical Culture in Product Teams
Sustainability in Product Management
  • Principles of Sustainable Product Design
  • Strategies for Green Product Development
  • Tools for Assessing Product Sustainability
  • Case Study: Tesla’s Sustainability Strategy
  • Measuring Environmental Impact
  • Integrating Sustainability into Product Lifecycle
  • Communicating Sustainability Efforts to Stakeholders
  • Addressing Challenges in Sustainable Development
Data-Driven Product Management
  • Role of Big Data and AI in Product Management
  • Leveraging Data for Strategic Decision-Making
  • Case Study: Data-Driven Strategy at Netflix
  • Implementing AI and Machine Learning in Products
  • Data Privacy and Security Concerns
  • Predictive Analytics for Product Planning
  • Managing Data Quality and Integrity
17
Phase 16: Product Design: Product Management and Lifecycle Strategies
Product Management and Lifecycle Strategies

Product Launch Strategies

  • Planning for a successful product launch
  • Supply chain coordination for manufacturing products
  • Marketing and sales strategies in manufacturing

Sustaining and Managing Product Lifecycle

  • Product updates and redesigns
  • Managing product obsolescence
  • Strategies for product end-of-life

Post-Launch Review and Continuous Improvement

  • Product performance analysis
  • Iterating based on customer feedback and performance data
18
Phase 17: Prompt Engineering & Generative AI in Product Management: Foundations, Applications, and Integration
Fundamentals of Generative AI and its Application in Product Management
  • What is Artificial Intelligence?
  • Machine Learning and Deep Learning
  • What is Generative AI?
  • Types of Generative AI Models
  • Training and Evaluation of Generative AI Models
  • Transfer Learning and Pre-trained Models
  • Advanced Generative AI Models – GANs
  • GAN Architecture and Advanced Training Techniques
  • What is Prompt Engineering?
  • Prompt Engineering example and Its Role
  • Role of Prompts in AI-powered Product Tools – Chatbots, Virtual Assistants
  • Prompt Engineering for Customer Insights – Tools: ChatGPT, Gemini
  • AI-driven Decision Making and Prompt Tuning – Tools: Figma with AI Plugin
  • Automating Product Workflows with Generative AI
  • Generative AI in Competitive Analysis and Market Insights
Working with Generative AI in Product Management
  • Prompt Engineering and Model Fine-Tuning
  • Introduction to Generative AI Creativity Tools
  • Integrating Generative and Discriminative Models
  • Ethical Considerations in Generative AI
  • Introduction to AI-powered Product Management
  • Working with Generative AI for Market Research
  • Working with Generative AI for Product Roadmaps
  • Working with Generative AI for Productivity
  • Working with Generative AI for Data Analytics
  • Working with Generative AI for Customer Engagement
  • Working with Generative AI for User Experience
19
Phase 18: Deep Dive in Advanced Product Management and Capstone Project
Strategic Business Case Studies
  • Google & Fitbit: Merging Data with Wearable Technology
    Examine Google’s acquisition of Fitbit to understand how data-driven strategies enable expansion into the health and fitness ecosystem. Analyze the strategic motivations, integration challenges, and market impact of this merger.
  • Microsoft & LinkedIn: Integrating Professional Networks
    Explore Microsoft’s acquisition of LinkedIn to assess how strategic integration of professional networking and productivity platforms creates synergistic value and strengthens Microsoft’s ecosystem.
Building AI Agents for Onboarding, Support, and Task Execution using n8n
  • Introduction to n8n: Understanding low-code automation and AI workflow orchestration for enterprise environments.
  • Designing intelligent workflows for employee onboardingcustomer support automation, and task execution using n8n nodes, triggers, and webhooks.
  • Integrating n8n with OpenAISlackGoogle Workspace, and CRM tools to build autonomous AI agents capable of decision-making and context-aware responses.
Capstone Project – Part 1
  • Defining Project Scope and Objectives
  • Conducting Market and User Research
  • Developing Initial Product Concept
  • Tools: Project Planning in Airtable, Trello
  • Case Study: Real-world Application Project from a Selected Industry
  • Establishing Project Milestones and Timelines
  • Resource Allocation and Budgeting
  • Initial Prototype Development and Feedback
Capstone Project – Part 2
  • Executing Product Development Strategy
  • Iterating Based on Feedback and Data
  • Tools: Product Analytics (Mixpanel)
  • Finalizing Product Features and Specifications
  • Conducting Usability Testing
  • Preparing for Product Launch
  • Gathering and Analyzing User Feedback
  • Continuous Improvement and Iteration
Capstone Project – Part 3
  • Final Presentation of Product Strategy and Analytics
  • Developing a Comprehensive Report
  • Tools: PowerPoint, Google Slides for Final Reports
  • Case Study: Presentation Strategies and Best Practices
  • Peer Review and Feedback Sessions
  • Evaluating Project Success and Lessons Learned
  • Applying Feedback for Final Refinements
  • Preparing for Real-world Implementation
Preparing for Product Management Interviews
  • Commonly Asked Product Management Interview Questions
  • Learn Problem-solving skills
  • Sessions on Improving Communication Skills
  • Stakeholder Management—Meaning and Techniques
20
Capstone Project
  • Hands-on project guided by industry mentor.
  • Apply real-world product management tools and strategies.
  • Showcase outcomes using valuation models, Excel, M&A or derivatives knowledge.
  • Get direct feedback, project review, and certification validation.
Internship
21
Career Support
Ongoing Throughout the Program.
  • Aptitude skill sessions & mock interviews.
  • Resume & LinkedIn profile building.
  • Interview readiness training by industry mentors.
  • Job opportunities via 400+ hiring partners.
  • Placement Readiness Test (PRT) to unlock interviews.
Placement Support Image

Certification

About IITM Pravartak

IITM Pravartak, a Technology Innovation Hub of IIT Madras is funded by the Department of Science and Technology, Government of India under its National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS), focuses on application-oriented research and innovation in the areas of SNACS. India’s first mobile operating system (BharOS) is developed by an IITM PravartakRead More..

Upon the completion of this program, you will receive:

  • Advanced Certification in Product Management with AI from IITM Pravartak.
IITM Advanced Certification in Product Management with AI Click to Zoom

Take the First Step to Join the Top 1% of Product Leaders in India!

Wanna know more about the admission process?
Admissions Ongoing for 2025.

Program Fee

Registration Fee Registration fees is non-refundable

₹2,000

Course Fee

₹1,33,000

Total Admission Fee

₹1,35,000 (Inclusive of All)

Upcoming Application Deadline 22nd Nov 2025

Class Timings: Sat-Sun 8:00 PM - 11.00 PM, Foundation Classes start from 22nd Nov 2025

Only limited seats are available. Apply early to secure your seat.

EMI Starts at

₹ 8000

We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs

Financing Partners

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The credit facility is provided by a third-party credit facility provider and any arrangement with such third party is outside Intellipaat’s purview.

In the News

Frequently Asked Questions

What can I expect from this Advanced Certification in Product Management with AI program?

This Advanced Certification in Product Management with AI course has been designed by top experts in the field with a deep understanding of industry requirements. The course covers various projects and assignments that will assist you in becoming job-ready and taking on challenging roles within the product management industry.

This Advanced Certification in Product Management with AI course offers numerous benefits. It provides in-depth knowledge of product management principles, strategies, and best practices through a comprehensive curriculum. Additionally, the course offers practical hands-on experience through real-world projects, industry insights from expert instructors, and valuable networking opportunities with fellow learners. By enrolling in this course, you can gain the skills and confidence needed to excel in the dynamic field of product management.

Advanced Certification in Product Management with AI offers a wide range of job opportunities, including product manager, product owner, product marketing manager, and strategic product planner. These roles exist in various industries and companies of all sizes. With the increasing demand for skilled product managers, the field provides promising career prospects and growth potential. There are 25,000+ job opportunities for professionals in India alone and over 260,000 job opportunities in the USA.

Upon completing this Advanced Certification in Product Management with AI, you unlock a wide range of career opportunities. As a certified product manager, you can pursue roles such as product manager, product strategist, product marketing manager, or even start your own product-oriented ventures. The scope extends across various industries, including technology, e-commerce, healthcare, finance, and more. You will be equipped to lead product development, drive innovation, and contribute to the success and growth of organizations.

The average salary for professionals in product management roles varies based on experience and industry. Generally, entry-level positions start from ₹6,00,000 per annum, while mid-level positions can range from ₹10,00,000 to ₹18,00,000 per annum. Senior roles, such as Senior Product Manager or Head of Product, can command salaries upwards of ₹25,00,000 per annum.

The course covers a wide range of topics, including the product life cycle, growth product management, product vision, strategy, and research, market research, pricing strategies, agile methodologies, user experience design, data analytics, and more. It also includes hands-on projects and case studies to provide practical experience.

The course is taught by experienced IIT / IIM faculty and industry experts with extensive experience in product management. Practitioners from leading companies also provide insights into real-world challenges and best practices.

Intellipaat is renowned for its high-quality product management training courses and industry mentorship. Our alumni have successfully secured positions in esteemed global organizations such as Amazon, Microsoft, Genpact, Sony, Gartner, and more. Additionally, learners gain lifetime access to free upgrades and course materials, providing ongoing support throughout their careers. By enrolling in a Advanced Certification in Product Management with AI course, you can take advantage of exclusive career guidance, interview preparation, and other valuable benefits.

Upon successful completion, you will receive an Advanced Certification in Product Management with AI from IITM Pravartak, which is recognized and valued in the industry.

The course is structured into various modules, each focusing on different aspects of product management. It is designed to be completed in 9 months, with a mix of online lectures, interactive workshops, and practical projects.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 9 months from the start date of your course.

Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in a real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.

Intellipaat actively provides placement assistance to all learners who have successfully completed the training. Intellipaat certification is recognized by over 3100 hiring companies around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.

Yes, Advanced Certification in Product Management with AI is highly valuable. It not only validates your expertise and knowledge in product management but also enhances your credibility in the job market. It demonstrates your commitment to professional growth and can significantly increase your chances of securing rewarding career opportunities in the field.

This Advanced Certification in Product Management with AI course introduces a range of industry-standard tools and platforms used in product management. These may include market research tools like surveys and customer feedback platforms, as well as data analytics software for analyzing product performance and user behavior, project management tools for organizing and tracking tasks, and collaboration platforms for seamless team communication and coordination.

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