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所在平台: Udemy |
课程主页: https://www.udemy.com/course/gcp-google-cloud-gcp-associate-data-practitioner-certification/
课程评论：没有评论
课程名称：GCP - Google Cloud Associate Data Practitioner Certification 课程概述：本课程是一个全面的实践学习路径，旨在帮助您为Google Cloud Associate Data Practitioner认证做准备，遵循官方考试指南中的结构和目标。该认证面向在云中处理数据的人员，要求具备管理、处理、分析和可视化数据的基础技能，使用Google Cloud技术。在本课程中，您将学习如何自信地在各种GCP服务中工作，并深入理解它们在端到端数据工作流中的实际应用。 重点内容： 1. **数据准备与导入**：学习区分ETL、ELT和ETLT，清洗和转换数据集，并熟悉Cloud Data Fusion和BigQuery等工具。 2. **数据分析与可视化**：使用BigQuery探索数据集，解读分析结果，并使用Looker Studio构建影响力强的仪表板。学习利用BigQuery ML和AutoML获取预测洞察。 3. **数据管道编排**：使用Cloud Composer（Apache Airflow）、Dataflow（Apache Beam）、Dataform和Dataproc来实施和调度数据管道。 4. **数据管理**：了解何时使用Cloud Storage、BigQuery、Cloud SQL、Firestore、Bigtable、Spanner和AlloyDB，并考虑成本、规模和性能等因素。 本课程将理论与实践实验、真实场景和基于项目的练习相结合，帮助您理解概念，增强信心。无论您是希望通过考试，还是希望在GCP中构建坚实的数据基础，本课程都提供了成功所需的一切内容。
This course is a comprehensive, hands-on learning path designed to help you prepare for the Google Cloud Associate Data Practitioner Certification, following the structure and objectives outlined in the official exam guide.The certification targets individuals working with data in the cloud, requiring foundational skills in managing, processing, analyzing, and visualizing data using Google Cloud technologies.In this course, you'll learn to confidently work across various GCP services and develop a clear understanding of their practical use in end-to-end data workflows.Key Focus Areas:Data Preparation and Ingestion: Learn to differentiate between ETL, ELT, and ETLT, clean and transform datasets, and work with tools like Cloud Data Fusion and BigQuery.Data Analysis and Visualization: Use BigQuery to explore datasets, interpret analytical results, and build impactful dashboards with Looker Studio. Learn to utilize BigQuery ML and AutoML for predictive insights.Data Pipeline Orchestration: Implement and schedule data pipelines using Cloud Composer (Apache Airflow), Dataflow (Apache Beam), Dataform, and Dataproc.Data Management: Understand when to use Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner, and AlloyDB, including considerations around cost, scale, and performance.This course blends theory with practical labs, real-world scenarios, and project-based exercises to help you internalize concepts and gain confidence.Whether you're aiming to clear the exam or build a strong data foundation in GCP, this course provides everything you need to succeed.
