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所在平台: Udemy |
课程主页: https://www.udemy.com/course/microsoft-azure-certifications-renew-mock-exam_dp-series/
课程评论：没有评论
**课程名称：** Microsoft Azure 认证续期模拟考试_DP 系列 **课程概述：** 本课程旨在帮助您准备 Microsoft Azure 数据工程师 (DP-203) 和数据科学与机器学习 (DP-100) 认证的续期。 **DP-203 (Azure 数据工程师) 认证详情：** * **目标人群：** 具有在各种结构化、非结构化和流式数据系统中集成、转换和整合数据以构建分析解决方案的专业知识的候选人。 * **核心职责：** * 通过数据探索帮助理解数据。 * 使用不同工具和技术构建和维护安全合规的数据处理管道。 * 利用各种 Azure 数据服务和框架存储和生成经过清洗和增强的数据集以供分析。 * 根据业务需求设计数据存储，包括现代数据仓库 (MDW)、大数据和 Lakehouse 架构。 * 确保数据管道和数据存储的高性能、高效、有组织和可靠运行。 * 识别和排除操作及数据质量问题。 * 设计、实施、监控和优化数据平台以满足数据管道需求。 * **必备知识：** * 熟练掌握数据处理语言，包括 SQL、Python 和 Scala。 * 理解并行处理和数据架构模式。 * 熟练使用以下 Azure 服务构建数据处理解决方案：Azure Data Factory、Azure Synapse Analytics、Azure Stream Analytics、Azure Event Hubs、Azure Data Lake Storage、Azure Databricks。 * **技能衡量：** * 设计和实施数据存储。 * 开发数据处理。 * 数据存储和数据处理的安全、监控与优化。 **DP-100 (数据科学与机器学习) 认证详情：** * **目标人群：** 具有在 Azure 上应用数据科学和机器学习来实施和运行机器学习工作负载的专业知识的候选人。 * **核心职责：** * 设计和创建适合数据科学工作负载的工作环境。 * 进行数据探索。 * 训练机器学习模型。 * 实施机器学习管道。 * 运行作业为生产做准备。 * 管理、部署和监控可扩展的机器学习解决方案。 * **必备知识：** * 具备使用 Azure Machine Learning 和 MLflow 进行数据科学的知识和经验。 * **技能衡量：** * 设计和准备机器学习解决方案。 * 探索数据和训练模型。 * 准备模型以进行部署。 * 部署和重新训练模型。 **课程内容：** 本课程将提供模拟考试，帮助您评估在上述两个认证领域所掌握的知识和技能，并针对性地进行复习和提升，以顺利通过认证续期。
DP-203 Certification detailsOverviewAs a candidate for this certification, you should have subject matter expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions.As an Azure data engineer, you help stakeholders understand the data through exploration, and build and maintain secure and compliant data processing pipelines by using different tools and techniques. You use various Azure data services and frameworks to store and produce cleansed and enhanced datasets for analysis. This data store can be designed with different architecture patterns based on business requirements, including:Modern data warehouse (MDW)Big dataLakehouse architectureAs an Azure data engineer, you also help to ensure that the operationalization of data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. You help to identify and troubleshoot operational and data quality issues. You also design, implement, monitor, and optimize data platforms to meet the data pipelines.As a candidate for this certification, you must have solid knowledge of data processing languages, including:SQLPythonScalaYou need to understand parallel processing and data architecture patterns. You should be proficient in using the following to create data processing solutions:Azure Data FactoryAzure Synapse AnalyticsAzure Stream AnalyticsAzure Event HubsAzure Data Lake StorageAzure DatabricksSkills measuredDesign and implement data storageDevelop data processingSecure, monitor, and optimize data storage and data processingDP-100 Certification detailsOverviewAs a candidate for this certification, you should have subject matter expertise in applying data science and machine learning to implement and run machine learning workloads on Azure.Your responsibilities for this role include:Designing and creating a suitable working environment for data science workloads.Exploring data.Training machine learning models.Implementing pipelines.Running jobs to prepare for production.Managing, deploying, and monitoring scalable machine learning solutions.As a candidate for this certification, you should have knowledge and experience in data science by using:Azure Machine LearningMLflowSkills measuredDesign and prepare a machine learning solutionExplore data and train modelsPrepare a model for deploymentDeploy and retrain a model
