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GenAI and LLMs on AWS · LearnSpace
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GenAI and LLMs on AWS

Курс от Duke University
Начальный≈ 46.2 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

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 pipelines to train, deploy and update models using AWS services Comply with regulations when deploying LLMs in production through techniques like differential privacy and controlled rollouts This course is unique in its focus on real-world operationalization of large language models using AWS. You will work through hands-on labs to put concepts into practice as you learn. Whether you are a machine learning engineer, data scientist or technical leader, you will gain practical skills to run LLMs in production.

Навыки, которые вы освоите

Amazon BedrockRust (Programming Language)Model TrainingModel EvaluationDevelopment EnvironmentLLM ApplicationLarge Language ModelingMLOps (Machine Learning Operations)Data EthicsAI SecurityGenerative AIServerless ComputingAI WorkflowsContinuous MonitoringCloud ComputingModel DeploymentAmazon Web Services

Программа курса

4 модулей · 100 учебных материалов

01Getting Started with Developing on AWS for AI44 материалов

Getting Started

Course IntroductionВидеоMeet your instructor: Noah GiftЧтениеCourse Structure and Discussion EtiquetteЧтениеMeet and Greet (Optional)Обсуждение

Учитесь у экспертов

Noah Gift

Executive in Residence and Founder of Pragmatic AI Labs

Alfredo Deza

Adjunct Assistant Professor in the Pratt School of Engineering

Derek Wales

Adjunct Professor

GenAI and LLMs on AWS
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Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 46.2 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Русский, Тайский, Индонезийский, Шведский, Турецкий, Испанский, Хинди, Японский, Казахский, Венгерский, Польский

Часть программы вашего университета
Report a problem with the courseЧтение

Introduction to AWS Cloud Computing for AI

Key TermsЧтениеAWS Cloud Adoption Framework for AIЧтениеCloud Service Model for AIВидеоCloud Deployment Model for AIВидеоBenefits of Cloud ComputingВидеоAWS Cloud Adoption Framework for AIВидеоQuiz-Introduction to AWS Cloud Computing for AIЗаданиеLesson ReflectionЧтение

Set Up AI Focused Development Environments

Key TermsЧтениеDevelopment Environments for AIВидеоMLOps Challenges and Opportunities in Rust and PythonВидеоGenerative AI Workflow for RustВидеоPython for Data Science in the Era of Rust and GenAIВидеоEmerging Rust LLMOps WorkflowsВидеоGetting Started with Code Catalyst for RustВидеоAWS SDK for RustЧтениеRust by ExampleЧтениеExternal Lab: AWS SDK S3 Bucket ListerЧтениеGetting Started with Sagemaker EditorВидеоLaunch a Code Editor application in StudioЧтениеGetting Started Lightsail for ResearchВидеоTutorial: Get started with Lightsail for Research virtual computers ЧтениеHello Rust StatementЛабораторнаяLesson ReflectionЧтениеQuiz-Set Up AI Focused Development EnvironmentsЗадание

Developing Serverless Solutions for Data, ML and AI

Key TermsЧтениеDiagram of Serverless with AWS Bedrock Service ВидеоDemo AWS Bedrock Knowledge AgentВидеоLLamaIndexЧтениеDemo AWS Bedrock CLIВидеоDiagram Serverless Options for RustВидеоDiagram Rust Axum Greedy Coin Microservice ComponentsВидеоDemo Rust Axum Greedy CoinВидеоDemo Rust Axum Docker WorkflowВидеоDistrolessЧтениеBuilding and Running Axum Greedy Coin MicroserviceЛабораторнаяLesson ReflectionЧтениеQuiz- Developing Serverless Solutions for Data, ML and AIЗадание

Module Wrap-up

Quiz-Getting Started with Developing on AWS for AIЗадание
02AI Pair Programming from CodeWhisperer to Prompt Engineering23 материалов

Prompt Engineering

Key TermsЧтение Prompt Engineering WorkflowsВидеоSummarizing Text with ClaudeВидеоPrompt EngineeringЧтениеPrompt Engineering with RustЛабораторнаяQuiz-Prompt EngineeringЗаданиеLesson ReflectionЧтение

Getting Started with CodeWhisperer

Key TermsЧтениеCodeWhisperer for Rust in Cloud9ВидеоCodeWhispererЧтениеLLMs for CodingЧтениеQuiz-CodeWhispererЗаданиеLesson ReflectionЧтение

CodeWhisperer for the Command-Line

Key TermsЧтениеInstall and ConfigureCodeWhisperer CLIВидеоCodeWhisperer for the CLIЧтениеUsing CodeWhisperer CLIВидеоBuilding Bash CLIВидеоBash FunctionsВидеоHands-on Project

Module Wrap-up

Quiz-AI Pair Programming from CodeWhisperer to Prompt EngineeringЗадание
03Amazon Bedrock23 материалов

What is Amazon Bedrock?

Key TermsЧтениеKey Components of Amazon BedrockВидеоWhat is Amazon Bedrock?ЧтениеLesson ReflectionЧтениеQuiz-Amazon BedrockЗаданиеExternal Lab: Amazon Bedrock Prompt Engineering ChallengeЧтение

Getting Started with the Bedrock SDK

Key TermsЧтениеExploring the Boto3 Bedrock Client Python SDKВидеоExploring the Cargo Rust SDKВидеоInvoking Python List ModelsВидеоExternal Lab Challenge: Python List Bedrock Foundation ModelsЧтениеInvoking Rust List ModelsВидеоLesson ReflectionЧтениеQuiz- Getting Started with the Bedrock SDKЗадание

Foundation Models, Knowledge Bases (RAG) and Agents with Bedrock

Key TermsЧтениеUsing Foundation ModelsЧтениеClaude3 Technical Deep Dive for BedrockЧтениеInvoking Claude via Bedrock Runtime APIВидеоAgents for Amazon BedrockЧтениеKnowledge BaseЧтение
04Project Challenges10 материалов

Challenge - From Rust Cargo Lambda to Bedrock Agents

Key TermsЧтениеIntroduction to Cargo LambdaВидеоCargo LambdaЧтениеBuilding Rust Add Function for AWS LambdaВидеоHands-on ProjectЛабораторнаяChallenge Lab-Bedrock AgentsЧтение

Challenge - Prompt Engineering for Rust Code with AWS GenAI Tools

External Lab: Prompt Engineering Rust ChallengeЧтение

Course Conclusion

Final Graded QuizЗаданиеNext StepsЧтениеShare your learning experienceЧтение
Лабораторная
Lesson ReflectionЧтение
Quiz-CodeWhisper for the Command-LineЗадание
External Lab: Invoking Foundation Models in Python with Boto3Чтение
Lesson ReflectionЧтение
Quiz-Foundation Models, Knowledge Bases (RAG) and Agents with BedrockЗадание