Packt

Introduction to Generative AI with Amazon Bedrock

Packt

Introduction to Generative AI with Amazon Bedrock

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Build conversational chatbots using Amazon Bedrock effectively

  • Implement RAG architecture for AI-driven information retrieval

  • Integrate safeguards and observability into AI applications

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Recently updated!

October 2026

Assessments

9 assignments

Taught in English

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There are 8 modules in this course

This module provides an overview of Generative AI, introduces course objectives, and guides learners through installing essential tools and libraries for working with AI projects on Amazon Bedrock.

What's included

2 videos1 assignment

This module provides an overview of Amazon Bedrock, its key features, and how it simplifies working with large language models. Learners will gain hands-on understanding of interacting with the Bedrock API through practical examples and demonstrations.

What's included

2 videos1 assignment

This module covers the design, implementation, and integration of conversational chatbots using Amazon Bedrock, along with the principles and application of Retrieval-Augmented Generation (RAG) to enhance AI interactions.

What's included

3 videos1 assignment

This module explores advanced applications of generative AI, including generating structured data, understanding AI agents, and creating multimodal content. Learners will gain practical skills in leveraging AI for diverse tasks and real-world scenarios.

What's included

3 videos1 assignment

This module introduces the core principles of Bedrock Data Automation, covering its role in streamlining AI workflows and improving efficiency. Learners will gain an understanding of how BDA can be applied in practical scenarios and explore real-world implementations through demonstrations.

What's included

2 videos1 assignment

This module explores how to implement observability and safeguards in AI applications, focusing on monitoring, reliability, and ethical constraints. Learners will gain practical skills in creating programmatic guardrails to ensure responsible AI behavior. The content emphasizes both technical and ethical aspects of AI system design.

What's included

2 videos1 assignment

This module equips learners with the skills to identify, analyze, and resolve common errors in generative AI applications. It provides practical problem-solving techniques and real-world examples to improve troubleshooting efficiency and effectiveness.

What's included

1 video1 assignment

This module offers practical exercises to reinforce learning, reviews real-world applications of generative AI, and provides additional insights and resources for further exploration of Amazon Bedrock.

What's included

3 videos2 assignments

Instructor

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