[Offer] [MULTI] Build Real World End-To-End Ai Agents Using Aws Bedrock

[nanid69781]

Build Real World End-To-End Ai Agents Using Aws Bedrock
Published 6/2025
Created by Sid Raghunath
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 52 Lectures ( 5h 57m ) | Size: 2.6 GB
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 build production-grade and real AI applications using AWS Bedrock. You will focus on building actual workflows using AWS Bedrock, KnowledgeBase and Workflows while leverage several other AWS Cloud components such as AWS Lambda, Dynamodb, Redshift, AWS ECS and many more. You'll work on real-world use cases across different domains covering everything from RAG and tool invocation to full multi-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 DiffusionImplement Retrieval-Augmented Generation (RAG) using:Amazon OpenSearch serverless for vector searchAmazon Redshift for structured groundingDesign real agentic applications that:Invoke tools and different application logic via AWS LambdaIntegrate with DynamoDB and S3Fetch or write data using custom logicBuild and deploy chatbots using Streamlit Set up multi-agent collaboration scenarios using AWS Bedrock. Trigger agents via REST APIs using API GatewayDeploy chatbots on AWS ECS using containerized workflowsThis course is not about theoretical lectures. It's for people who want to ship AI systems to 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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