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Home > Technical Courses > Artificial Intelligence > Developing Generative AI Applications on AWS
Learn to build and customize AI solutions by using Amazon Bedrock programmatically.
In this advanced two-day course, software developers learn to build and customize AI solutions by using Amazon Bedrock programmatically. Through hands-on exercises and labs, participants will invoke foundation models through Amazon Bedrock APIs, implement Retrieval Augmented Generation (RAG) patterns with Amazon Bedrock Knowledge Bases, and 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.
Category
ID
Duration
Level
Price
Artificial Intelligence
13985
2 Day(s)
Intermediate
$1,390.00
Objectives
• 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.
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
Questions?
We recommend that attendees of this course have: • Generative AI Essentials on AWS • Intermediate-level proficiency in Python • Familiarity with AWS Cloud
Developing Generative AI Applications on AWS
Class Schedule
Live Online
Course Overview
Training Delivery Methods
With Productivity Point, you will have a spectrum of delivery methods to choose from... when where and how you like it. Whether it's in a classroom or online, we have a delivery option to meets your needs.
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Private Group
On Demand
Classroom Live Training
Get in-person, hands-on instruction with live lab exercises taught by subject matter experts who deliver authorized and industry-leading content.
With classrooms in almost every major U.S. city, Productivity Point has something for users of every level, so you can earn the most popular industry certifications. You get hands-on learning experience with live lab exercises taught by experienced instructors. We proudly advocate our learning services to be hosted by the best-qualified trainers in terms of technical knowledge and teaching skills.
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Private Group Training
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On-Demand Learning
On-Demand is an IT training solution designed around your schedule, budget, and learning needs. Combining high-quality video, reading, and knowledge checks in a self-paced format, On-Demand helps you build skills as your schedule allows—all at once or five minutes at a time.
With On-Demand, you learn at your own pace and in the convenience of your own space.
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