Creating AI Agents on AWS
Sowjanya Pandruju, Cloud Application Architect at AWS, teaches you how to develop and deploy AI agents using AWS.
Sowjanya Pandruju
สร้างบัญชีฟรีของคุณ
ฝึกฝนและตรวจสอบความก้าวหน้าของคุณ
ดำเนินการต่อด้วย Googleเมื่อดำเนินการต่อ ถือว่าคุณยอมรับ ข้อกำหนดการใช้งานและ นโยบายความเป็นส่วนตัว และยอมรับว่าข้อมูลของคุณจะถูกจัดเก็บในสหรัฐอเมริกาที่เกี่ยวข้อง
บทแนะนำ
AWS Multi-Agent Orchestrator: A Guide With Examples
Learn how to set up the AWS Multi-Agent Orchestrator framework and build a demo project focused on multi-agent orchestration.
บทแนะนำ
AWS Generative AI: How to Deploy, Govern, and Scale Solutions
A deep dive into how AWS generative AI powers scalable, secure, and cost-optimized AI applications across industries. Ideal for teams ready to move from pilot to production.
บทแนะนำ
The Complete Guide to Machine Learning on AWS with Amazon SageMaker
This comprehensive tutorial teaches you how to use AWS SageMaker to build, train, and deploy machine learning models. We guide you through the complete workflow, from setting up your AWS environment and creating a SageMaker notebook instance to preparing data, training models, and deploying them as endpoints.

As AI agents move from experiments to production, engineering teams are looking for cloud-native tools that can support real-world deployment at scale. AWS offers a flexible and powerful ecosystem for building, orchestrating, and scaling AI agents—if you know where to start.
In this code-along, Sowjanya Pandruju, Cloud Application Architect at AWS, teaches you how to develop and deploy AI agents using AWS. You’ll explore the core architecture of modern agents, walk through essential AWS services, and learn how to take your project from prototype to production. This session is ideal for AI engineers looking to operationalize their agent workflows.
Key Takeaways:
Session Resources (Including GitHub Repo)