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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/mlops-aws-azure-duke
课程评论:没有评论
课程名称:MLOps 平台:亚马逊 SageMaker 和 Azure ML 课程概述:在《MLOps 平台:亚马逊 SageMaker 和 Azure ML》课程中,您将学习在两大云平台(亚马逊网络服务 AWS 和微软 Azure)上构建、训练和部署机器学习解决方案所需的技能。该课程也非常适合准备 AWS 或 Azure 机器学习认证的人士,或者希望从事数据科学家、软件工程师、软件开发人员等工作的用户。 课程大纲: 1. 数据工程与 AWS 技术 - 本周您将学习如何在 AWS 上构建数据工程解决方案,并通过使用 AWS Step Functions 和 AWS Lambda 构建数据工程管道来应用所学。 2. 探索性数据分析与 AWS 技术 - 本周您将使用 AWS 技术构建数据工程解决方案,并通过构建数据科学笔记本来应用学习内容。 3. 建模与 AWS 技术 - 本周您将使用 AWS 技术构建机器学习建模解决方案,并通过在命令行工具中运行线性回归模型来进行应用。 4. MLOps 与 AWS 技术 - 本周您将学习如何使用 AWS 技术部署和运行机器学习解决方案,并通过在 SageMaker Studio Lab 中微调 Hugging Face 模型来进行应用。 5. 机器学习认证 - 本周您将学习主要云服务提供商的机器学习认证,以及如何将其应用于 MLOps。您将了解与机器学习和 ML 工程任务相关的服务,例如 AutoML,以及它们如何与认证内容相结合。 这个课程将为您提供在现代云计算环境中进行高效机器学习操作的全面知识和实践经验。
Name:Data Engineering with AWS Technology
Description:This week you will learn how to build data engineering solutions on AWS and apply it by building a data engineering pipeline with AWS Step Functions and AWS Lambda.
Name:Exploratory Data Analysis with AWS Technology
Description:This week you will compose data engineering solutions using AWS technology and apply it by building data science notebooks.
Name:Modeling with AWS Technology
Description:This week you will compose machine learning modeling solutions using AWS technology and apply it by building a linear regression model that runs inside a command-line tool.
Name:MLOps with AWS Technology
Description:This week you will learn to deploy and operationalize machine learning solutions using AWS technology and apply it by fine-tuning a Hugging face model using Sagemaker Studio Lab.
Name:Machine Learning Certifications
Description:This week you will learn about Machine Learning certifications from the major cloud providers and how to apply them to MLOps. You will learn about services related to Machine Learning and ML Engineering tasks like AutoML and how they apply to the certifications.
In MLOps (Machine Learning Operations) Platforms: Amazon SageMaker and Azure ML you will learn the necessary skills to build, train, and deploy machine learning solutions in a production environment using two leading cloud platforms: Amazon Web Services (AWS) and Microsoft Azure. This course is also a great resource for individuals looking to prepare for AWS or Azure machine learning certifications or who are working (or seek to work) as data scientists, software engineers, software developers,