About the Instructor
AWS Training
Official AWS ML education from the team behind SageMaker. Covers production infrastructure used by 1M+ AWS customers globally. Updated with latest managed services and best practices.
First Principles
The cloud abstracts away infrastructure. Instead of managing GPUs and servers, you call managed services: SageMaker for training, Lambda for inference.
AI Ecosystem Fit
Layer 3 (Cloud) — Infrastructure is the foundation of everything. Understanding how to deploy, scale, and monitor models on AWS is non-negotiable for production engineers.
Prerequisites
What Paid Projects This Unlocks
Deploy production agents: serverless AI agents on AWS Lambda, SageMaker endpoints, managed ML services. Scale agents to production.
3 Client Projects You Can Get Paid For
Real businesses have this problem right now. Build it, pitch it, charge for it.
Stack This With → (Unlocks Higher-Paying Projects)
Build end-to-end pipelines (training → deployment)
Monitor models in production
Optimize costs for scale
Why This Matters
You can't productionize agents without understanding deployment. AWS is where most Fortune 500 companies run their AI.