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Microsoft AI-Powered Product Management Certification

AI-Powered Product Management Course

AI-Powered Product Management

Think Like a Product Leader, Solve Real Product Problems and Build AI-Native Products

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AI-powered Product Management Certification

AI Product Management Course Curriculum

Curriculum

1. Module 1: AI -Augmented PM Fellowship 

Week 1: Product Thinking, Discovery & Data Foundations

Product mindset

Why products exist

Product thinking vs feature thinking

Product discovery frameworks

AI-powered market research using Perplexity and Genspark

Synthetic persona building with Claude

User segmentation and customer segmentation

AI-assisted SQL for user data retrieval to Visualize app performance with data

Case Study

Define success metrics for a productivity app using AI-simulated behavior

Week 2: AI-Powered Design & Root Cause Analysis

Product design framework
User journey mapping
Feature prioritization
Solution tradeoffs
Text-to-wireframe conversion using Figma AI
UI component generation with AI
Root Cause Analysis
RCA frameworks
Metrics drop investigation using Mixpanel Spark AI
Natural-language analytics querying
Automated RCA Boards and property-level breakdowns
Anomaly Detection and Session Replay correlation

Hands-on: Designing a new feature for a learning platform using AI-driven solution tradeoffs. The Mixpanel Lab: Diagnosing a simulated 25% drop in user engagement by correlating Anomaly Detection alerts with Session Replays to see exactly where users are struggling

Week 3 : PRD Automation & Product Improvement

Product gap identification

User feedback analysis

Scope definition

Prioritization

Success metrics

PRD structure & PRD generation using ChatPRD and WriteScribe

Automated documentation from raw notes

Sentiment-tracking pipelines for feedback loops

Case Study

Improve a grocery delivery experience by identifying product gaps with AI

Week 4: Product Teardown + Job Profiling

Hands-on Product Teardown:

Spotify, Notion, Airbnb

AI-powered competitor UX pattern analysis and AI-generated portfolio teardown reports. Portfolio building workshop and portfolio structure

Resume review using AI-powered ATS simulators

LinkedIn optimization

2. Module 2: Building AI-Native Products

Week 5: AI Foundations & Feasibility for PMs

AI vs ML vs LLM and AI use case discovery

AI feasibility thinking, AI feature design

Understanding Tokenization and context windows and the cost-benefit analysis of LLM providers

Week 6: LLM APIs & Agentic Workflows

Prompt engineering and LLM fundamentals

Introductions to LLM APIs and HuggingFace models

Hands-on lab: building an automation pipeline connecting an LLM to external data sources

Week 7: AI Architecture & Agentic Design

AI agents, AI copilots, AI system design

Architecture tech for PMs Understanding RAG (Retrieval-Augmented Generation) vs. Fine-tuning and data pipelines and model deployment basics.

Hands-on lab: : Designing a multi-agent system (e.g., using Flowise or n8n) where agents collaborate on complex tasks.

Week 8: Capstone – Building the AI MVP

Finalize AI MVP and prepare for the job market

Capstone Presentation: Demonstrating a functional AI prototype built with low-code tools (e.g., an AI-driven assessment tool or personalized tutor).

Final Review: Mock interviews and portfolio finalization focusing on "AI-First" product management.

AI-Powered Product Management FAQs

Frequently Asked Questions

Course

Course FAQs

1. Who is this program for? Do I need prior product management experience?

This program is designed for a range of learners; aspiring PMs looking to break into product roles, working professionals wanting to strengthen product thinking, and existing PMs aiming to integrate AI into their workflows or move into strategic/AI-native product roles. There are no strict eligibility criteria. What matters most is a strong interest in product thinking, problem-solving, and a willingness to learn through structured frameworks, real cases, and hands-on exercises.

2. Do I need a technical or coding background to learn the AI portion?

No. The program is built for product managers, not engineers. You'll learn AI concepts (LLMs, tokenization, RAG vs. fine-tuning, agentic workflows) from a PM lens — focused on feasibility, use-case discovery, and feature design. Hands-on labs use low-code and no-code tools like Flowise, n8n, ChatPRD, Figma AI, and Mixpanel Spark, so you can build a working AI MVP without writing production code.

3. What does the curriculum actually cover?

The 8-week program is split into two modules. Module 1 (Weeks 1–4): AI-Augmented PM Fellowship covers product thinking, discovery, design, root cause analysis, PRD writing, product teardowns, and portfolio building — all augmented with AI tools. Module 2 (Weeks 5–8): Building AI-Native Products covers AI foundations, LLM APIs, prompt engineering, agentic workflows, AI system design, and culminates in a capstone where you build and present a functional AI MVP.

4. How is the learning delivered? Is it live or self-paced?

Sessions are live and instructor-led, with interactive discussions around real product examples. Each topic follows a consistent structure: framework explanation → case exercise → individual assignment → mock interview. This ensures you build practical skills rather than just absorbing theory.

5. What will I have to show for it at the end of the program?

You'll graduate with a tangible product portfolio that includes Product Requirement Documents (PRDs), product teardown analyses of companies like Spotify, Notion, and Airbnb, product improvement case studies, and a functional AI MVP built during the capstone. The final weeks also include resume reviews using AI-powered ATS simulators, LinkedIn optimization, and mock interviews focused on AI-first product roles.

6. Which AI tools will I get hands-on experience with?

You'll work with a broad stack used in modern product workflows: Perplexity and Genspark for market research, Claude for synthetic persona building, Figma AI for text-to-wireframe design, Mixpanel Spark AI for analytics and root cause analysis, ChatPRD and WriteScribe for PRD automation, LLM APIs and HuggingFace models for building features, and Flowise or n8n for designing multi-agent systems.

7. How does this help me prepare for product management interviews and roles?

Interview prep is embedded throughout the program, not bolted on at the end. Every session ends with mock interviews on the topic just covered. Week 4 includes a dedicated portfolio building workshop and job profiling — resume reviews, LinkedIn optimization, and hands-on teardowns of top products. The final week focuses entirely on mock interviews and portfolio finalization tuned for "AI-First" PM roles.

8. What certification will I receive on completing the program?

On successful completion, you'll receive an industry-recognized Microsoft certification, validating your skills in AI-powered product management. This adds credibility to your profile and signals to hiring managers that you've been trained on a curriculum aligned with industry standards in AI and product development.

AI-Powered Product Management Course

AI-Powered Product Management

Think Like a Product Leader, Solve Real Product Problems and Build AI-Native Products

Why Choose Our AI-Powered Product Management Program

First-Principles Product Thinking

Practical Learning Approach

AI-Focused Product Skills

Product Portfolio Creation

AI-Powered Product Management Certificate

AI-Powered Product Management Certification

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