Build Real world End-to-End AI Agents using AWS Bedrock
Published 6/2025
Duration: 5h 58m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 2.60 GB
Genre: eLearning | Language: English
Published 6/2025
Duration: 5h 58m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 2.60 GB
Genre: eLearning | Language: English
Hands-on course to build Real Agentic AI systems using AWS Bedrock, Python, Lambda, Redshift, Dynamodb and OpenSearch
What you'll learn
- Data Engineers and Architects looking to integrate LLMs into real-world cloud workflows using AWS Bedrock
- AI/ML Engineers who want to build production-grade agentic systems with Bedrock and several other AWS Services
- Cloud Developers interested in deploying RAG-based chatbots, tools, and automations on AWS infrastructure
- Technical professionals seeking hands-on product-grade experience with Bedrock models like Claude, Titan, and Stable Diffusion
Requirements
- Prior coding experience in Python
- Prior experience in AWS as a software or data engineer
- AWS Account
Description
This course is designed for engineers, data professionals, and software developers who want to buildproduction-gradeandreal AI applicationsusingAWS Bedrock. You will focus on building actual workflows using AWS Bedrock, KnowledgeBase and Workflows while leverage several other AWS Cloud components such asAWS Lambda, Dynamodb, Redshift, AWS ECSand many more.
You’ll work on real-world use cases across different domains covering everything from RAG and tool invocation to fullmulti-agent orchestration. The course follows a code-first, deployable approach using core AWS services.
What you’ll build and learn:
Use Bedrock APIs to query models like Claude, Titan, and Stable Diffusion
Implement Retrieval-Augmented Generation (RAG) using:
Amazon OpenSearch serverlessfor vector search
Amazon Redshiftfor structured grounding
Design real agentic applications that:
Invoke tools and different application logic viaAWS Lambda
Integrate withDynamoDBandS3
Fetch or write data using custom logic
Build and deploy chatbots usingStreamlit
Set upmulti-agent collaborationscenarios using AWS Bedrock.
Trigger agents via REST APIs usingAPI Gateway
Deploy chatbots onAWS ECSusing containerized workflows
This course is not about theoretical lectures. It’s for people who want toship AI systemsto AWS cloud infrastructure , backed by hands-on examples that work end-to-end.
Who this course is for:
- Technical professionals who want to move beyond basic prompt usage and build real-world AI systems using AWS Bedrock
- Data Engineers, ML/Ops Engineers, and Cloud Developers looking to integrate LLMs like Claude, Titan, or Stable Diffusion into production workflows
- Engineers interested in orchestrating AI agents, tool invocations, and workflows using Lambda, DynamoDB, Redshift, and OpenSearch
- Developers who want to build RAG pipelines grounded in structured and unstructured enterprise data
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