AI Product Management Masterclass

Build, Lead, and Ship AI Products with Confidence - even if you're not technical.

25+

Hands-on Modules

Core Sections

Real AI Product Built

1-1 Coaching Sessions

Complete Curriculum

Technical Foundations

Master ML, Deep Learning, and GenAI from a product-first lens.

Module 1: Classical Machine Learning for PMs

Supervised vs. unsupervised learning, core models (Logistic Regression, Decision Trees, XGBoost), ML lifecycle, evaluation metrics (precision, recall, F1, AUC), real-world use cases (churn, fraud, personalization).

Module 2: Deep Learning Foundations

Neural networks, CNNs for vision, RNN/LSTMs for sequences, limitations (data hunger, cost, explainability).

Module 3: GenAI & Transformer Architecture

How Transformers work (attention, decoder stacks), tokenization, logits, temperature, top-p, top-k, embeddings, fine-tuning, prompt engineering, OpenAI vs. open-source, fine-tuning vs. RAG vs. adapters.

Module 5: Prompts and Prompt Engineering

Prompt basics, prompt templates, prompt chaining, prompt evaluation, prompt best practices for LLMs and GenAI products.

Module 6: AI Agents

Introduction to AI agents, agent frameworks, multi-agent collaboration patterns, use cases, and product implications.

Module 7: Model Context Protocol

Understanding the Model Context Protocol (MCP): how context is managed and passed to models, best practices for context window management, and implications for product design and user experience.

Module 8: Infrastructure & Cost Fundamentals

Inference vs. training cost, GPUs, cold starts, caching, serverless deployment, token pricing, latency impact.

AI Product Management

Lead cross-functional teams to build AI that works, ethically and effectively.

Module 1: What Makes AI PM Different?

Deterministic vs. probabilistic products, non-linear iterations and fuzzy MVPs, AI features vs. traditional features.

Module 2: The AI Product Lifecycle

Framing AI problems (prediction, classification, generation), data availability → modeling → feedback loop, shipping v1 with uncertainty, success metrics: product vs. model KPIs.

Module 3: Collaborating with ML/GenAI Teams

Role clarity: PM vs. data scientist vs. ML engineer, writing ready PRDs, prompt tension and QA workflows, working with model uncertainty.

Module 4: AI Product Requirements

Defining clear and actionable requirements for AI products. Translating business objectives into technical specifications. Managing evolving requirements. Prioritizing AI features. Best practices for documenting and communicating AI product requirements.

Module 5: Responsible AI & Risk

Bias, fairness, explainability. Regulatory (GDPR, CCPA, OpenAI usage policies). Mitigating hallucinations and abuse. Ethical UX: disclaimers, confidence scoring, user control.

Module 6: AI Product Design

Designing intuitive AI experiences, user research for AI products, prototyping AI features, and managing user expectations with probabilistic outputs.

Module 7: AI Product Metrics

Evaluation metrics (for PMs): precision, recall, latency, coverage. LLM-specific: helpfulness, prompt sensitivity, token usage. Monitoring in production: drift, feedback loops, retraining signals.

Instructor-Led Step By Step AI Product Development

Apply what you've learned to build a real, working AI product with direct instructor guidance.

Module 1: Scoping & Planning

Choose a solvable AI problem (classification? generation?), define your user, workflow, and data needs, write a lightweight AI PRD (problem, data, model, UX).

Module 2: Dataset & Model Strategy

Source your dataset (Kaggle, scraping, simulation). Choose model approach: ML (scikit-learn) or GenAI (OpenAI API or OSS model). Prototyping in notebooks, LangChain, or Hugging Face.

Module 3: UX, Prompts & Feedback

AI UX patterns: confidence, retries, user override. Prompt design: system vs. user prompts. Real-time feedback loops: thumbs up/down, rating prompts. Deploy via Streamlit or Vercel.

Module 4: Monitoring & Iteration

Add observability: latency, helpfulness, usage. Model versioning, prompt A/B testing. Drift detection and prompt retraining.

AI PM Capstone Project

Showcase your mastery by building and presenting your own AI product from 0 to 1.

Project Part 1: Project Ideation & Scoping

Define a solvable AI problem, identify your target user and their workflow, and outline initial data needs. Craft a lightweight AI Product Requirements Document (PRD) covering problem, data, model, and user experience.

Project Part 2: Data & Model Prototyping

Source your dataset (e.g., Kaggle, scraping, simulation). Choose model approach: ML (scikit-learn) or GenAI (OpenAI API or OSS model). Prototyping in notebooks, LangChain, or Hugging Face environments.

Project Part 3: UX & Feedback Loop Design

Design intuitive AI UX patterns, including confidence indicators, retry mechanisms, and user override options. Develop effective prompt designs (system vs. user prompts) and implement real-time feedback loops like thumbs up/down or rating prompts.

Project Part 4: Deployment & Monitoring

Deploy your AI product prototype using platforms like Streamlit or Vercel. Set up basic observability for key metrics such as latency, helpfulness, and usage. Implement initial model versioning and prompt A/B testing strategies.

Project Part 5: Iteration & Presentation

Iterate on your product based on user feedback and monitoring signals. Prepare a comprehensive demo walkthrough of your AI product. Write a project reflection or mini case study, and optionally record a 60-second product pitch to showcase your work.

Find Your Next AI Product Job and Build Your Next AI Startup

Leverage your new skills to advance your career in AI product management or launch your own venture.

Module 1: Navigating the AI PM Job Market

Crafting an AI PM resume, interview strategies for AI product roles, networking in the AI ecosystem, and identifying key companies hiring AI PMs.

Module 2: Launching Your AI Startup

Ideation to MVP for AI startups, securing early funding, building a founding team, and scaling your AI venture.

1-on-1 AI Product Management Coaching

Accelerate your career transition with personalized guidance from an industry expert.

Session 1: Career Path & Skill Gap Analysis

A 30-minute personalized session to assess your current skills, identify gaps, and map out a clear path to becoming a successful AI Product Manager.

Session 2: Resume & Interview Strategy

A 30-minute deep dive into optimizing your resume for AI PM roles and developing winning interview strategies, including behavioral and technical questions.

Session 3: Networking & Job Search Tactics

A 30-minute session focused on effective networking in the AI ecosystem, leveraging LinkedIn, and advanced job search techniques to land your dream AI PM role.

Meet Your Instructor

Ata Tahiroglu

AI/ML Group Product Manager @ Apple

Columbia University Lecturer

Ata is a seasoned AI/ML Group Product Manager at Apple with extensive experience building cutting-edge AI products at scale. He has lectured over 2k students over the last 4 years. Based in the San Francisco Bay Area, he brings real-world expertise from one of the world's leading technology companies to help you master the art and science of AI product management.

Next Cohort

August 2nd - August 30th, 2025

Saturdays, 8:00 AM-2:00 PM PST

Timezone: America / Los Angeles

6-hour live online session

Including 30 min break

Limited spots available. Secure your place today!

July 22nd - August 21st, 2025

Mondays and Wednesdays, 5:30 PM-8:30 PM

Timezone: America / Los Angeles

3-hour live online session

Including short break

Limited spots available. Secure your place today!

Why This Masterclass?

Product-First Approach

Gain a unique product-first understanding of ML, Deep Learning, and GenAI, focusing on practical application and strategic implications, not just technical theory.

Hands-on Experience

Build two real AI products from scratch, including an instructor-led project and your own Capstone Project, ensuring tangible, portfolio-ready experience.

End-to-End Skills

Master the entire AI product lifecycle, from technical foundations and team leadership to deployment, monitoring, and even launching your own AI startup or finding your next AI PM job.

Find Your Next AI Product Role

Benefit from a dedicated session on crafting an AI PM resume, interviewing strategies, and networking to secure your ideal role in the AI industry.

Build Your Next AI Startup

Receive expert guidance on ideation, MVP development, securing early funding, and scaling your own venture, turning your innovative ideas into reality.

Technical Acumen for Non-Technical PMs

Transform into a technically savvy product manager or founder by gaining a core conceptual understanding of AI technologies, enabling effective collaboration and strategic decision-making.

Tools You Will Master

V0

A powerful no-code AI development platform that enables you to build, test, and deploy custom AI applications without writing code. Ideal for rapid prototyping and validating AI product concepts.

N8N

An extensible workflow automation platform for integrating AI services. Create sophisticated AI pipelines, automate data processing, and connect multiple AI tools in a visual interface.

Cursor

An AI-enhanced code editor that revolutionizes development workflow. Features intelligent code completion, automated refactoring, and context-aware suggestions powered by advanced language models.

Claude MCP

A cutting-edge language model optimized for multi-context processing. Excel at complex reasoning, content generation, and sophisticated AI interactions with enhanced context understanding.

Huggingface

The go-to platform for ML model deployment and sharing. Access a vast ecosystem of pre-trained models, deploy custom solutions, and leverage state-of-the-art AI research tools.

Openrouter

A smart API routing and management solution for AI services. Efficiently handle multiple AI model endpoints, balance loads, and optimize request routing for scalable AI applications.

What Our Students Are Saying

"This masterclass transformed my understanding of AI product development. The hands-on projects were invaluable, and the instructor's real-world insights were truly inspiring."

Jane Doe

Senior Product Manager, Tech Company

"I came in with a traditional PM background and left feeling confident about leading AI initiatives. The curriculum is incredibly practical and directly applicable to today's AI landscape."

John Smith

Product Lead, AI Startup

"The Capstone Project was a game-changer. Building a real AI product from scratch, with expert guidance, gave me the confidence and portfolio piece I needed to advance my career."

Emily White

Aspiring AI Product Manager