- Information Engineering
- Google Cloud
- Bigquery
- Tensorflow
- Cloud Computing
- Google Cloud Platform
备考 Google Cloud 认证:云数据工程师 专业证书
Advance your career in data engineering
提供方
您将学到的内容有
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.
您将获得的技能
关于此 专业证书
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.
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
专业证书是什么?
塑造技能,做好工作准备
无论您是想开始新的职业生涯,还是改变目前职业,Coursera 专业证书都能帮您为开始工作做好准备。选择最适合的时间和地点,自行安排学习进度。立即注册,探索新的职业道路,可免费试用 7 天。您可以随时暂停学习或结束订阅。
实践项目
将您的技能应用到实践项目,并丰富您的简历内容,进而向潜在雇主展示您已为开始工作做好准备。您需要成功完成项目以获得证书。
获得职业证书
当完后计划中的所有课程后,您将获得一张证书。您可以将其在专业网络上分享,并获得使用职业支持资源的权限,这能够为您开启职业生涯提供助力。许多招聘合作伙伴认可我们的许多专业证书,并且我们还有许多合作伙伴可以帮助您准备认证考试。您可以在适用的各个专业证书页面上找到更多信息。

此专业证书包含 6 门课程
Google Cloud Big Data and Machine Learning Fundamentals
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
Modernizing Data Lakes and Data Warehouses with Google Cloud
The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
Building Batch Data Pipelines on GCP
Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
Building Resilient Streaming Analytics Systems on Google Cloud
Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud using QwikLabs.
提供方

Google 云端平台
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
常见问题
退款政策是如何规定的?
我可以只注册一门课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
How long does it take to complete the Professional Certificate?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
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