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.


Amazon Bedrock Customization, Optimization & Automation
本课程是 AWS Generative AI for Developers 专业证书 的一部分



位教师:Morgan Willis
包含在 中
您将学到什么
Model Fine-tuning
Performance Optimization
Automated Evaluation
您将获得的技能
要了解的详细信息

添加到您的领英档案
July 2025
3 项作业
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该课程共有2个模块
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.
涵盖的内容
5个视频3篇阅读材料1个作业
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.
涵盖的内容
8个视频6篇阅读材料2个作业1个插件
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常见问题
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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