Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.

Preparing for Google Cloud Certification: Cloud Data Engineer 专业证书

Advance your career in data engineering

位教师：Google Cloud Training

103,703 人已注册

包含在 Coursera Plus 中

了解更多

5 门课程系列

获得职业证书，展示您的专业知识

4.6

（7,123 条评论）

中级等级

推荐体验

4 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

5 门课程系列

获得职业证书，展示您的专业知识

4.6

（7,123 条评论）

中级等级

推荐体验

4 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.
Employ BigQuery to carry out interactive data analysis.
Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.
Choose between different data processing products on Google Cloud.

要了解的详细信息

可分享的证书

添加到您的领英档案

行业认证

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

专业认证 - 5门课程系列

Google Cloud Professional Data Engineer certification was ranked #1 on Global Knowledge's list of 15 top-paying certifications in 2021! Enroll now to prepare!

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87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification.

Here's what you have to do

1) Complete the Coursera Data Engineering Professional Certificate

2) Review other recommended resources for the Google Cloud Professional Data Engineer certification exam

3) Review the Professional Data Engineer exam guide

4) Complete Professional Data Engineer sample questions

5) Register for the Google Cloud certification exam (remotely or at a test center)

Applied Learning Project

This professional certificate incorporates hands-on labs using Qwiklabs platform.These hands on components will let you apply the skills you learn. Projects incorporate Google Cloud Platform products used within Qwiklabs. You will gain practical hands-on experience with the concepts explained throughout the modules.

应用的学习项目

This Professional Certificate incorporates hands-on labs using our Qwiklabs platform.

These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google BigQuery, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.

Modernizing Data Lakes and Data Warehouses with Google Cloud

第 1 门课程8小时

您将学到什么

Differentiate between data lakes and data warehouses.
Explore use-cases for each type of storage and the available data lake and warehouse solutions on Google Cloud.
Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.
Examine why data engineering should be done in a cloud environment.

您将获得的技能

类别：Google Cloud Platform

类别：Data Warehousing

类别：Data Lakes

类别：Cloud Storage

类别：Data Processing

类别：Big Data

类别：Data Infrastructure

类别：Data Pipelines

类别：Cloud Engineering

类别：SQL

类别：Scalability

Building Batch Data Pipelines on Google Cloud

第 2 门课程17小时

您将学到什么

Review different methods of data loading: EL, ELT and ETL and when to use what
Run Hadoop on Dataproc, leverage Cloud Storage, and optimize Dataproc jobs
Build your data processing pipelines using Dataflow
Manage data pipelines with Data Fusion and Cloud Composer

您将获得的技能

类别：Data Pipelines

类别：Apache Spark

类别：Google Cloud Platform

类别：Data Transformation

类别：Data Processing

类别：Apache Hadoop

类别：Extract, Transform, Load

类别：Apache Airflow

类别：Data Integration

类别：Serverless Computing

类别：Big Data

类别：Data Migration

Building Resilient Streaming Analytics Systems on Google Cloud

第 3 门课程8小时

您将学到什么

Interpret use-cases for real-time streaming analytics.
Manage data events using the Pub/Sub asynchronous messaging service.
Write streaming pipelines and run transformations where necessary.
Interoperate Dataflow, BigQuery and Pub/Sub for real-time streaming and analysis

您将获得的技能

类别：Data Processing

类别：Performance Tuning

类别：Data Pipelines

类别：Google Cloud Platform

类别：Real Time Data

类别：Data Transformation

类别：SQL

类别：Big Data

类别：Scalability

Smart Analytics, Machine Learning, and AI on Google Cloud

第 4 门课程6小时

您将学到什么

Differentiate between ML, AI and deep learning.
Discuss the use of ML API’s on unstructured data.
Execute BigQuery commands from notebooks.
Create ML models by using SQL syntax in BigQuery and without coding using Vertex AI AutoML.

您将获得的技能

类别：Google Cloud Platform

类别：Applied Machine Learning

类别：Machine Learning

类别：Unstructured Data

类别：Jupyter

类别：Artificial Intelligence

类别：Data Pipelines

类别：Tensorflow

类别：Big Data

类别：MLOps (Machine Learning Operations)

Preparing for your Professional Data Engineer Journey

第 5 门课程4小时

您将学到什么

List the domains covered on the Professional Data Engineer (PDE) certification exam.
Identify gaps in your knowledge and skills for each domain.

您将获得的技能

类别：Data Storage

类别：Data Processing

类别：Google Cloud Platform

类别：Data Analysis

类别：Automation

类别：Data Security

类别：Data Pipelines

类别：Data Management

类别：Data Infrastructure

类别：Data Maintenance

类别：Cloud Storage

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Google Cloud Training

Google Cloud

1,978 门课程3,620,726 名学生

提供方

Google Cloud

人们为什么选择 Coursera 来帮助自己实现职业发展

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自 2018开始学习的学生

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Jennifer J.

自 2020开始学习的学生

''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

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自 2021开始学习的学生

''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'

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无限制访问 10,000+ 世界一流的课程、实践项目和就业就绪证书课程 - 所有这些都包含在您的订阅中

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常见问题

This Professional Certificate is designed to be completed in three and a half months at five hours per week.

One (1) year of experience with one or more of the following:

• A common query language such as SQL

• Extract, transform, load activities

• Data modeling

• Machine learning and/or statistics

• Programming in Python

We strongly recommend you take these courses in order, beginning with Big Data and Machine Learning Fundamentals. This is especially important when completing the Qwiklabs projects, as these hands-on labs build upon the work you complete in preceding courses.