Foundations of Serverless AI Agents: AWS Lambda & Cloud Run

As AI agents become essential for automating complex tasks, knowing how to deploy them efficiently in the cloud is a highly sought-after skill. Many developers know how to build basic AI scripts, but struggle to host them in a way that scales automatically and remains cost-effective. This course bridges the gap between artificial intelligence and cloud engineering. You will start by understanding the core concepts of agentic AI and serverless computing, then move step-by-step through the process of taking an AI agent from a local environment to a production-ready, scalable deployment. By exploring modern cloud paradigms, you will learn how to run intelligent workloads without the overhead of managing traditional servers. What you'll learn: - Understand fundamental AI agent terminology, capabilities, and basic retrieval-augmented generation (RAG) patterns. - Configure serverless environments on AWS Lambda and Cloud Run for scalable execution. - Apply container fundamentals to package your AI models and dependencies reliably. - Implement basic infrastructure-as-code (IaC) principles to manage and replicate your deployments. - Practice setting up modern observability to monitor agent performance and troubleshoot errors. - Deploy intelligent workflows that respond to external triggers and API requests. The curriculum begins with foundational definitions of AI agents and serverless computing before progressing into written, practical deployment exercises. You will read through clear architectural patterns and configuration snippets to build your deployment skills incrementally. Designed for beginners and aspiring cloud engineers, this course requires no prior cloud hosting or AI deployment experience. Start your journey into serverless AI deployment today and build the skills to host intelligent agents in the cloud.