AI Product Management Curriculum

Master the fundamentals of machine learning that power modern AI products. Learn to distinguish between supervised and unsupervised learning approaches, understand industry standard models like Logistic Regression, Decision Trees, and XGBoost, and grasp the complete ML lifecycle from data preparation to deployment. Discover how to evaluate model performance using precision, recall, F1 scores, and AUC metrics while exploring real world applications in customer churn prediction, fraud detection, and personalization engines that drive business value.

Dive into the neural network architectures that revolutionized AI capabilities. Understand how Convolutional Neural Networks (CNNs) excel at computer vision tasks, how Recurrent Neural Networks (RNNs) and LSTMs process sequential data for applications like language understanding and time series prediction. Learn to identify when deep learning is the right solution and when to consider alternatives, balancing the power of these models against their data requirements, computational costs, and explainability constraints.

Unlock the technology behind ChatGPT, Claude, and other cutting edge generative AI systems. Explore the transformer architecture's attention mechanism that enables unprecedented language understanding, master key concepts like tokenization, logits, temperature, top p, and top k sampling that control AI outputs. Learn practical techniques for prompt engineering, understand the trade offs between OpenAI's commercial APIs and open source alternatives, and discover when to use fine tuning, Retrieval Augmented Generation (RAG), or parameter efficient adapters for your specific use case.

Become a master of prompt engineering the critical skill for building effective GenAI products. Learn to craft precise, effective prompts that consistently produce high quality outputs. Explore advanced techniques including prompt templates for standardization, prompt chaining for complex multi step workflows, and rigorous prompt evaluation methodologies. Discover industry best practices that separate amateur implementations from production ready AI products, ensuring your applications deliver reliable, valuable results to end users.

Step into the future of AI with autonomous agents that can plan, reason, and execute complex tasks. Understand the architectural patterns that enable AI agents to break down problems, use tools, and make decisions. Learn hands-on how to build AI agents using N8N, a powerful workflow automation platform that enables sophisticated agent architectures. Explore leading agent frameworks and discover multi agent collaboration patterns where specialized agents work together to solve sophisticated challenges. Learn to identify compelling use cases for agent based solutions and understand the product implications of deploying autonomous AI systems.

Master the Model Context Protocol (MCP) a crucial framework for building sophisticated AI applications. Learn how to leverage Claude MCP to implement powerful context management patterns that enable seamless integration between AI models and external data sources. Understand how context is efficiently managed and passed to language models, and explore best practices for optimizing context window usage to balance information retention with cost and performance. Discover how thoughtful context management directly impacts user experience, enabling more coherent conversations, better task completion, and more satisfying AI interactions in your products.

Gain essential knowledge of AI infrastructure economics and architecture that separates successful products from failed experiments. Understand the critical differences between inference and training costs, learn how GPUs power AI computations, and discover strategies to manage cold starts and leverage caching for optimal performance. Master serverless deployment patterns, navigate token based pricing models, and learn to balance latency requirements with cost constraints skills essential for building scalable, profitable AI products.

Discover why managing AI products requires a fundamentally different mindset than traditional software. Learn to embrace probabilistic outputs instead of deterministic guarantees, navigate non linear iteration cycles where progress isn't always straightforward, and define "Minimum Viable Products" when AI models have fuzzy performance boundaries. Understand how AI features fundamentally differ from traditional features in planning, execution, and user experience essential knowledge for any PM leading AI initiatives.

Master the complete journey from AI concept to production deployment. Learn to expertly frame business problems as prediction, classification, or generation tasks that AI can solve. Understand the critical path from data availability assessment through modeling to establishing sustainable feedback loops. Develop confidence in shipping version 1 despite inherent model uncertainty, and learn to define meaningful success metrics that separate product level KPIs from model level performance indicators a crucial distinction for driving business impact.

Build the collaboration skills that make or break AI product teams. Gain clarity on the distinct but complementary roles of Product Managers, Data Scientists, and ML Engineers. Learn to write comprehensive, AI ready Product Requirements Documents that technical teams can execute against. Master the art of managing prompt tension balancing model capability with user expectations and develop effective QA workflows for systems with probabilistic outputs. Transform uncertainty into opportunity by learning proven strategies for working productively with AI's inherent variability.

Learn to craft crystal clear, actionable requirements that set AI products up for success. Master the art of translating high level business objectives into precise technical specifications that engineers and data scientists can implement. Develop frameworks for managing evolving requirements as models improve and use cases expand. Learn sophisticated prioritization techniques tailored to AI features, balancing innovation with feasibility. Discover best practices for documenting and communicating AI product requirements that align stakeholders and accelerate development.

Master the critical skills of defining data and model requirements for AI products. Learn to identify and source quality datasets from platforms like Kaggle, ensuring you have the right data foundation for your product vision. Develop expertise in evaluating and selecting appropriate models from Hugging Face's vast ecosystem, understanding trade-offs between performance, cost, and deployment complexity. Discover how to specify data quality requirements, define model performance thresholds, and establish clear acceptance criteria that bridge product requirements with technical implementation. Learn to communicate effectively with data scientists and ML engineers about data needs, model selection, and performance expectations.

Navigate the critical ethical and regulatory landscape of AI products with confidence. Understand how bias emerges in AI systems and learn practical strategies to identify and mitigate it. Master fairness principles and explainability techniques that build user trust. Stay ahead of evolving regulations including GDPR, CCPA, and AI specific policies from providers like OpenAI. Learn proven approaches to mitigate hallucinations and prevent abuse. Design ethical user experiences with appropriate disclaimers, confidence scoring, and user controls that balance AI capability with responsible deployment.

Master the unique challenges of designing intuitive experiences for AI powered products. Learn specialized user research techniques that uncover how people interact with AI systems and what they truly need. Develop skills in prototyping AI features that manage user expectations while showcasing capability. Discover frameworks for handling probabilistic outputs gracefully in user interfaces, transforming uncertainty from a liability into a feature. Create products that users trust and love by designing experiences that acknowledge AI's strengths and limitations honestly.

Develop expertise in the metrics that matter for AI product success. Master evaluation metrics that Product Managers must understand: precision and recall for classification, latency for user experience, and coverage for feature completeness. Learn LLM specific metrics including helpfulness scores, prompt sensitivity analysis, and token usage optimization. Build robust monitoring systems for production AI, including drift detection that catches degrading performance, feedback loop analysis, and data driven retraining triggers. Transform metrics into actionable insights that continuously improve your product.

Unlock the power of AI-assisted development through vibe coding, a revolutionary approach that enables non-technical product managers to build functional prototypes. Learn to leverage tools like V0, Cursor, and Claude to rapidly translate product ideas into working code without deep programming knowledge. Master the art of describing what you want in natural language and iterating with AI to refine implementations. Discover how to prototype user interfaces, build basic functionality, and create interactive demos that bring your product vision to life. Understand the capabilities and limitations of AI-assisted coding, enabling you to move faster from concept to tangible prototype while maintaining effective collaboration with engineering teams.

Master go-to-market strategies tailored for AI products. Learn to craft compelling positioning that communicates AI value without overwhelming users with technical complexity. For B2B use cases, discover how to build scalable email marketing campaigns using tools like Instantly to reach decision-makers, personalize outreach at scale, and drive qualified leads through AI-powered automation. For B2C applications, explore AI-native advertising strategies including dynamic creative optimization, predictive audience targeting, and automated campaign management that maximize ROI. Develop frameworks for building trust through transparent communication about AI capabilities and limitations. Learn to measure marketing effectiveness through AI-specific metrics including feature adoption rates, user engagement patterns, and conversion optimization strategies that drive sustainable growth.

Position yourself for success in the competitive AI PM job market. Learn to craft resumes that showcase AI specific skills and experiences that hiring managers seek. Master interview strategies tailored to AI product roles, including how to discuss technical concepts, demonstrate product thinking, and showcase your unique value. Develop networking approaches that work in the AI ecosystem, from engaging with AI communities to building relationships with practitioners. Identify high growth companies actively hiring AI PMs and understand what they're looking for in candidates.

Turn your AI product vision into a thriving startup venture. Master the journey from initial ideation through Minimum Viable Product (MVP) development for AI powered startups. Learn proven strategies for securing early stage funding, from articulating your vision to investors to understanding what VCs look for in AI startups. Discover how to build a balanced founding team that combines product vision, technical expertise, and business acumen. Develop frameworks for scaling your AI venture sustainably while maintaining product quality and team culture.

Receive personalized guidance to accelerate your AI PM career trajectory. In this focused 30 minute session, work one on one with an experienced AI product leader to assess your current skill set objectively, identify critical gaps blocking your progress, and chart a clear, actionable path forward. Receive customized recommendations on learning priorities, experience building opportunities, and strategic career moves that align with your unique background and goals transforming generic advice into a personalized roadmap for success in AI product management.

Transform your professional materials and interview approach with expert coaching. Spend 30 minutes working directly with a seasoned AI product leader to optimize your resume, ensuring it highlights AI relevant experiences and speaks the language hiring managers understand. Develop winning interview strategies covering both behavioral questions that reveal your product thinking and technical questions that test your AI knowledge. Learn to tell compelling stories about your work, articulate your value proposition clearly, and handle challenging questions with confidence.

Master the networking and job search strategies that land elite AI PM roles. In this focused 30 minute coaching session, learn to build an influential presence in the AI ecosystem through strategic networking. Discover how to leverage LinkedIn effectively going beyond basic connections to become a recognized voice in AI product management. Learn advanced job search techniques including how to access hidden opportunities, navigate recruiter relationships, and position yourself as an ideal candidate. Get personalized tactics tailored to your unique background and target companies.