AI PM
AI PM Learning Roadmap 2026
Complete guide to becoming an AI Product Manager. Learn ML fundamentals, LLM product management, and AI ethics. Salary: $180K-$600K+.
What is an AI Product Manager?
AI PMs build products powered by machine learning, LLMs, and AI. They bridge technical ML teams and business stakeholders, making decisions about data, models, and AI UX. Critical skills: ML fundamentals (not expert-level), model evaluation, AI ethics, and product sense.
Phase 1: AI/ML Fundamentals (2-3 months)
Understand core AI/ML concepts without deep math.
Machine Learning Basics
- Supervised vs Unsupervised
- Classification vs Regression
- Training/Test/Validation splits
- Overfitting/Underfitting
Common ML Algorithms
- Linear Regression
- Decision Trees
- Random Forests
- Neural Networks basics
ML Workflow
- Data collection
- Feature engineering
- Model training
- Evaluation metrics
- Deployment
Recommended Resources
- AI For Everyone (Andrew Ng) — 12h Free
- Machine Learning Crash Course (Google) — 15h Free
- The Hundred-Page Machine Learning Book — $30
Phase 2: Deep Learning & LLMs (2-3 months)
Understand modern AI (neural nets, transformers, LLMs).
Deep Learning Fundamentals
- Neural networks
- Backpropagation
- CNNs
- RNNs
- Transformers
Large Language Models
- GPT architecture
- Prompting techniques
- Fine-tuning
- RAG (Retrieval)
- Context windows
LLM Product Patterns
- Chatbots
- Copilots
- Agents
- Summarization
- Classification
Recommended Resources
- Deep Learning Specialization (Coursera) — 3mo $49/mo
- Building LLM Applications (DeepLearning.AI) — 10h Free
- OpenAI Cookbook — Ongoing Free
Phase 3: AI Product Management (2-3 months)
Learn AI-specific PM skills and frameworks.
Model Evaluation
- Accuracy/Precision/Recall
- F1 score
- AUC-ROC
- Confusion matrix
- Model performance monitoring
Data Strategy
- Data collection
- Labeling
- Synthetic data
- Data pipelines
- Privacy/GDPR
AI Ethics & Bias
- Fairness metrics
- Bias detection
- Explainability (XAI)
- Safety
- Responsible AI
AI Product Metrics
- Model drift
- Latency
- Throughput
- Cost per inference
- Human-in-loop
Phase 4: Technical Skills (1-2 months)
Gain hands-on technical credibility.
Python Basics
- Variables, loops, functions
- Pandas (data analysis)
- Working with APIs
- Jupyter notebooks
ML Tools
- OpenAI API
- Langchain
- Vector databases (Pinecone)
- MLOps basics
Prompt Engineering
- Zero-shot
- Few-shot
- Chain-of-thought
- System prompts
Types of AI PM Roles
ML Infrastructure PM
- Build platforms for ML teams
- Google, Meta, Amazon
- $200K-$500K
AI Application PM
- Build AI-powered features
- All tech companies
- $180K-$400K
LLM Product PM
- Build with GPT/Claude
- OpenAI, Anthropic, startups
- $200K-$600K
AI Ethics/Safety PM
- Ensure responsible AI
- OpenAI, Google, Meta
- $220K-$500K
Related Resources
Master These with a Coach
The cohort covers all of this with live feedback from FAANG PMs.