Developing Generative AI Applications on AWS Training Course | CourseMonster
- CMDBID 1037
- Course Code AMWSGAIA
- Duration 2 Days
AWS Course
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Overview
Developing Generative AI Applications on AWSis a practical training course for teams that need structured, instructor-led skills in Developing Generative, Applications, AWS Describe. CourseMonster has rewritten this summary to make the page clearer for learners, managers and search engines while preserving the key learning outcomes.
This course is designed to introduce generative artificial intelligence (AI) to software developers interested in using large language models (LLMs) without fine-tuning. The course provides an overview of generative AI, planning a generative AI project, getting started with Amazon Bedrock, the foundations of prompt engineering, and the architecture patterns to build generative AI applications using Amazon Bedrock and LangChain.
Activities
This course includes presentations, demonstrations, and group exercises
. Explore more AI traininghereUseful links: AWS Training and Certification | Project Management training at CourseMonster | CourseMonster course page
CourseMonster SEO course note: Developing Generative AI Applications on AWS Training Course | CourseMonster has been positioned as a practical AWS learning pathway for teams that need searchable, role-based training outcomes rather than a generic course description. The page now highlights Developing, Generative, Applications, AWS, CourseMonster, certification readiness, workplace application and visible next-step links so learners can compare this course with related CourseMonster programmes.The course is listed as 2 day(s), making it suitable for structured team scheduling.It is especially relevant for it professionals, system administrators, developers, analysts, architects and technical specialists responsible for implementing or supporting the technology covered in this course.
Related CourseMonster courses: AWS Certification Exam Readiness Workshop AWS Certified Solutions Architect Professional | Amazon AWS exam prep workshop - AWS Certified SysOps Administrator | GIAC Security Essentials (GSEC)
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Audience
Skills Gained
Useful links: AWS Training and Certification | Project Management training at CourseMonster | CourseMonster course page
Additional workplace outcomes: Participants can explain where Developing Generative AI Applications on AWS Training Course | CourseMonster fits in a wider AWS skills roadmap, identify related certifications or follow-on courses, and apply the concepts to real project, operations or service delivery scenarios.
Prerequisites
Outline
- Describe generative AI and how it aligns to machine learning
- Define the importance of generative AI and explain its potential risks and benefits
- Identify business value from generative AI use cases
- Discuss the technical foundations and key terminology for generative AI
- Explain the steps for planning a generative AI project
- Identify some of the risks and mitigations when using generative AI
- Understand how Amazon Bedrock works
- Familiarize yourself with basic concepts of Amazon Bedrock
- Recognize the benefits of Amazon Bedrock
- List typical use cases for Amazon Bedrock
- Describe the typical architecture associated with an Amazon Bedrock solution
- Understand the cost structure of Amazon Bedrock
- Implement a demonstration of Amazon Bedrock in the AWS Management Console
- Define prompt engineering and apply general best practices when interacting with foundation models (FMs)
- Identify the basic types of prompt techniques, including zero-shot and few-shot learning
- Apply advanced prompt techniques when necessary for your use case
- Identify which prompt techniques are best suited for specific models
- Identify potential prompt misuses
- Analyze potential bias in FM responses and design prompts that mitigate that bias
- Identify the components of a generative AI application and how to customize an FM
- Describe Amazon Bedrock foundation models, inference parameters, and key Amazon Bedrock APIs
- Identify Amazon Web Services (AWS) offerings that help with monitoring, securing, and governing your Amazon Bedrock applications
- Describe how to integrate LangChain with LLMs, prompt templates, chains, chat models, text embeddings models, document loaders, retrievers, and Agents for Amazon Bedrock
- Describe architecture patterns that you can implement with Amazon Bedrock for building generative AI applications
- Apply the concepts to build and test sample use cases that use the various Amazon Bedrock models, LangChain, and the Retrieval Augmented Generation (RAG) approach
Useful links: AWS Training and Certification | Project Management training at CourseMonster | CourseMonster course page
Suggested learning path: After this course, compare related options via the links in the overview and the AWS training category.
Certification
Labs - Please note: The labs for your AWS course will be delivered through AWS Builder labs. In order to access these labs you will need to have an Amazon BuilderID. You can set up your new Amazon account here. Please ensure that you have set up this Amazon BuilderID in advance of attending your class.
Courseware – Please note: In order to access your digital course materials you are required to set up a Gilmore account in advance of attending your course. To do this please follow this link.
Please also be aware that in order to access your materials and Labs it is important that your device and network should not restrict access to AWS or Vitalsource content. For that reason, AWS recommend NOT using a Corporate laptop with any security restrictions in place or the use of a VPN.
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