Overview
Developing Generative AI Applications on AWS
What will you get from this course:
- Learn to build and customize AI solutions by using Amazon Bedrock programmatically
- Invoke foundation models through Amazon Bedrock APIs
- Implement Retrieval Augmented Generation (RAG) patterns with Amazon Bedrock Knowledge Bases
- Develop AI agents with tool integration
The course focuses on the practical implementation of prompt engineering techniques, responsible AI practices with Amazon Bedrock Guardrails, open source framework integration, and architectural patterns for real-world business applications.
This course includes presentations, demonstrations, hands-on labs, and group exercises.
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Why Choose KORNERSTONE
- Accredited, practitioner-led, expert certificate trainers to provide high quality training
- Official training material included
- Practical, scenario-based learning – focus on application, not just theory
- Excellent Passing Rate
Skills Covered
In this course, you will learn to:
- Develop generative AI applications using Amazon Bedrock.
- Design architecture patterns of generative AI applications.
- Configure Amazon Bedrock APIs to invoke foundation models (FMs) programmatically.
- Develop agentic AI applications by integrating Amazon Bedrock tools and open source frameworks.
- Build custom solutions with Retrieval Augmented Generation (RAG) and Amazon Bedrock Knowledge Bases.
- Integrate open source SDKs with Amazon Bedrock to build business.
- Optimize model responses by applying prompt engineering techniques.
- Evaluate generative AI application components.
- Implement responsible AI practices to protect generative AI.
Prerequisites
We recommend that attendees of this course have:
- Completed the Generative AI Essentials AWS instructor-led course
- Intermediate-level proficiency in Python
- Familiarity with AWS Cloud
Target Audience
This course is intended for:
- Software developers interested in leveraging large language models without fine-tuning
Course Curriculum
Module 1: Exploring Components of Generative AI Applications on AWS
- Understanding generative AI concepts
- Identifying AWS generative AI stack components
- Designing generative AI application components
Module 2: Programming with Amazon Bedrock
- Guiding model response generation
- Using Amazon Bedrock programmatically
- Hands-on lab: Develop with Amazon Bedrock APIs
- Hands-on lab: Develop Streaming Patterns with Amazon Bedrock APIs
Module 3: Applying Prompt Engineering for Developers
- Introducing prompt engineering
- Introducing prompt techniques
- Optimizing prompts for better results
Module 4: Using Amazon Bedrock APIs in Common Architectures
- Implementing architecture patterns with Amazon Bedrock APIs
- Exploring common use cases
- Adding conversational memory to extend context
- Hands-on lab: Develop Conversation Patterns with Amazon Bedrock APIs
Module 5: Customizing Generative AI Responses with RAG
- Implementing Retrieval Augmented Generation (RAG)
- Using Amazon Bedrock Knowledge Bases
- Hands-on lab: Develop Retrieval Augmented Generation (RAG) Applications with Amazon Bedrock Knowledge Bases
Module 6: Integrating Open Source Frameworks with Amazon Bedrock
- Invoking a foundation model in Amazon Bedrock using LangChain
- Using LangChain for context-aware responses
- Hands-on lab: Develop a Generative AI Application Pattern using Open Source Frameworks and Amazon Bedrock Knowledge Bases
Module 7: Evaluating Generative AI Application Components
- Evaluating application components
- Evaluating model output
- Evaluating RAG output
- Optimizing latency and cost
- Hands-on lab: Evaluating Retrieval Augmented Generation (RAG) Applications
Module 8: Implementing Responsible AI
- Understanding responsible AI
- Mitigating bias and addressing prompt misuses
- Using Amazon Bedrock Guardrails
- Hands-on lab: Securing Generative AI Applications Using Bedrock Guardrails
Module 9: Using Tools and Agents in Generative AI Applications
- Using tools
- Understanding AI agents
- Understanding open source agentic frameworks
- Understanding agent interoperability
Module 10: Developing Amazon Bedrock Agents
- Implementing Amazon Bedrock Flows
- Designing Amazon Bedrock Agents
- Developing Amazon Bedrock Inline Agents
- Designing multi-agent collaboration
- Using Amazon Bedrock AgentCore
- Hands-on lab: Developing Amazon Bedrock Agents Integrated with Amazon Bedrock Knowledge Bases and Guardrails
Dates & Locations
September 10, 2026 - September 11, 2026
October 8, 2026 - October 9, 2026
November 19, 2026 - November 20, 2026
December 10, 2026 - December 11, 2026
Exam & Certification
There is no exam directly associated with this course. However, AWS offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2026 and beyond. Achieving AWS credentials is one of the most effective ways to validate your skills and accelerate your career.
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- Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity — areas driving global digital transformation.
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- Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.
Explore our top AWS Certifications for 2026 and start building the skills that matter today.
