Udemy – Generative AI on AWS – Amazon Bedrock, RAG & KIRO [2026] 2025-9

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Description

Generative AI on AWS – Amazon Bedrock, RAG & KIRO [2026] This course is a comprehensive, project-based program for learning Generative AI on the AWS cloud platform that teaches learners how to build production-ready applications using Amazon Bedrock, the RAG architecture, and the AWS KIRO tool. This course is designed by a leading instructor and experienced AWS architect to take learners from the basics of AI and Machine Learning to building large-scale, enterprise-scale applications. The main goal of this course is to facilitate the career change of learners and help them enter high-paying positions in the fields of Generative AI and Agentic AI. The training process starts with basic concepts such as Prompt, Inference, Context Window, and how Foundation Models work, and then goes into an in-depth examination of the Amazon Bedrock service, architecture, pricing, and inference parameters. A distinctive feature of this course is its special focus on real-world and practical projects from the world of technology. During the course, learners will implement three major projects: building a specialized equipment assistant using a Serverless architecture and adhering to the principles of Responsible AI and Guardrails, implementing the RAG training program based on Agentic AI, and developing the FleetMate application with the new AWS KIRO tool. In addition, topics such as model evaluation, personalization and fine-tuning, monitoring with CloudWatch, transforming concepts from the PoC stage to a real-world deployable state, as well as reviewing the basics of Python, AWS Lambda, and API Gateway are covered in a completely practical way so that all participants can turn their theoretical knowledge into practical skills in the job market.

What you will learn

Thorough understanding of AI, Machine Learning, Generative AI, Foundation Models, Prompts, Tokens, and Inference concepts
Understanding the Amazon Bedrock architecture and how to access basic models through Bedrock Runtime
Designing production-ready GenAI architectures using AWS Lambda, API Gateway, and CloudWatch services
Implementation of a real project for a specialized equipment assistant (from PoC stage to Production)
Building a Serverless RAG e-Learning Application with Amazon Bedrock
FleetMate application development using AWS KIRO and the Agentic AI intelligent development environment
Implementing the principles of model evaluation, Responsible AI, Guardrails, and system monitoring
Understand the concepts of document processing, chunking, embeddings, vector search, and information retrieval in the RAG architecture.
Building Augmented Generation Retrieval-based Applications with Amazon Bedrock Knowledge Bases
Review and learn practical concepts of the Python programming language, AWS Lambda, and API Gateway

This course is suitable for people who:

Software developers and engineers who plan to build Generative AI applications with Amazon Bedrock
AWS professionals, Cloud engineers, and system architects who want to design GenAI operational architectures
AI and ML professionals looking for hands-on experience building RAG and enterprise applications on AWS
Learners who have built GenAI prototypes and plan to turn them into final products
Anyone interested in learning Generative AI on AWS from basics to advanced real-world projects

Generative AI on AWS – Amazon Bedrock, RAG & KIRO Course Details [2026]

Publisher: Udemy
Instructor: Rahul Trisal
Training level: Beginner to advanced
Training duration: 13 hours and 9 minutes

Course syllabus as of 2026/10

Generative AI on AWS - Amazon Bedrock, RAG & KIRO [2026]

Prerequisites for Generative AI on AWS – Amazon Bedrock, RAG & KIRO [2026]

Basic familiarity with AWS cloud.
No prior Generative AI experience is required. We start with the fundamentals.
Basic Python/Any programming knowledge is recommended for the hands-on development sections.