AWS Artificial Intelligence Practitioner Learning Plan

Learning Path: MLOps / AI Infrastructure Engineer

MLOps Engineers bridge the gap between data scientists who build models and the production systems where those models run. They design and maintain the infrastructure, pipelines, and processes that allow models to be trained, evaluated, versioned, deployed, monitored, and retrained reliably.

Learning Path: AI Product Manager

AI Product Managers define what AI-powered products to build, why, and for whom. They work at the intersection of business strategy, user needs, and AI capabilities — translating what AI can do into products that create real value. They combine traditional PM skills with deep AI literacy.

Learning Path: Data Engineer (AI Pipelines)

Data Engineers build and maintain the infrastructure that collects, stores, transforms, and serves data to AI and ML systems. The AI Pipelines specialisation means focusing on reliable, scalable pipelines that feed training data to models and serve inference-time data to production AI applications. Without good data engineering, ML models cannot be trained or serve real users.