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Amazon Bedrock Customization, Optimization & Automation

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Amazon Bedrock Customization, Optimization & Automation

This course is part of AWS Generative AI and AI Agents with Amazon Bedrock Professional Certificate

Instructors: Russell Sayers

2,960 already enrolled

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

32 reviews

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

32 reviews

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Model Fine-tuning
Performance Optimization
Automated Evaluation

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments

Taught in English

91% of learners achieved a positive career outcome

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Build your Cloud Computing expertise

This course is part of the AWS Generative AI and AI Agents with Amazon Bedrock Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Amazon Web Services

There are 2 modules in this course

Grow generative AI expertise with this course focusing on customizing, optimizing, and automating AI solutions using Amazon Bedrock. This course is designed for developers who want to fine-tune their AI applications for peak performance and efficiency.

You'll begin by exploring model customization techniques, including fine-tuning and continued pre-training. Learn how to adapt foundation models to your specific use cases, enhancing their performance on domain-specific tasks. The course then dives into advanced optimization strategies. You'll work with Bedrock Evaluation Jobs to assess and compare model performance, implement prompt caching for improved response times, and utilize prompt routing for efficient model selection. In the automation section, you'll discover how to streamline AI workflows using Bedrock Data Automation. This tool will enable you to process and transform large datasets. Throughout the course, you'll work in hands-on labs and real-world scenarios, applying these advanced techniques to solve complex AI challenges. By the conclusion of the course, you'll be designing, implementing, and maintaining AI solutions, stretching the limits of what's possible with generative AI on AWS. Please note: The hands-on exercises are optional and require access to your own AWS account. Completing these activities may result in minimal usage charges.

Module details

This module explores how developers can improve the output of foundation models using customization techniques in Amazon Bedrock. You will learn about fine-tuning with labeled data, continued pretraining with domain-specific content, and model distillation for cost-effective performance. The module also introduces LangChain to enhance AI workflows. You will gain practical knowledge to tailor models to their specific use cases and boost relevance and accuracy.

What's included

5 videos3 readings1 assignment

In this module, you will learn how to improve the efficiency and scalability of generative AI applications using Amazon Bedrock. You will use Bedrock Evaluation Jobs for comparing model responses, and apply prompt caching and routing to optimize performance. The module also covers automation techniques using Bedrock Data Automation and Amazon Q Developer on the command line. By the end, you will be equipped to streamline inference, automate tasks, and make intelligent deployment decisions.