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GenAI and LLMs on AWS

Duke University via Coursera

Coursera based on 20 ratings

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Overview

This course will teach you how to deploy and manage large language models (LLMs) in production using AWS services like Amazon Bedrock. By the end of the course, you will know how to: Choose the right LLM architecture and model for your application using services. Optimize cost, performance and scalability of LLMs on AWS using auto-scaling groups, spot instances and container orchestration Monitor and log metrics from your LLM to detect issues and continuously improve quality Build reliable and secure...

Syllabus

  • Getting Started with Developing on AWS for AI
    • This module, you will learn how to set up a Rust development environment, utilize the AWS SDK for Rust, and build AWS Lambda functions with Rust.
  • AI Pair Programming from CodeWhisperer to Prompt Engineering
    • CodeWhisperer writes code. You learn to guide it. Large language models crunch data, spit out content. Chain-of-thought prompts make models explain themselves. Craft prompts, shape outputs. Build CLI tools, bash functions. Use CodeWhisperer CLI to automate tasks. Fast, efficient coding with AI.
  • Amazon Bedrock
    • This module, learn Amazon Bedrock capabilities. Apply through model evaluations and customizations.
  • Project Challenges
    • In this module, you will challenge yourself to apply the concepts covered in the previous module and challenge yourself to apply what you learned in a new context.
GenAI and LLMs on AWS
Go to Class

Duke University via Coursera

21 hours 56 minutes

Paid Certificate Available

English

On-Demand

Beginner

Instructor

Noah Gift

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