TensorflowBigqueryGoogle Cloud PlatformCloud Computing
Data Engineering, Big Data, and Machine Learning on GCP 專項課程
Google 云端平台数据工程. Launch your career in Data Engineering. Deliver business value with big data and machine learning.
15,068 人已註冊
提供方
您將學到的內容有
Processing big data at scale for analytics and machine learning
Fundamentals of building new machine learning models
Creating streaming data pipelines and dashboards
您將獲得的技能
關於此 專項課程
94,770 次近期查看
This online specialization provides participants a hands-on introduction to designing and building data pipelines on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and derive insights. The course covers structured, unstructured, and streaming data.
This course teaches the following skills:
• Design and build data pipelines on Google Cloud Platform
• Lift and shift your existing Hadoop workloads to the Cloud using Cloud Dataproc.
• Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow
• Manage your data Pipelines with Data Fusion and Cloud Composer.
• Derive business insights from extremely large datasets using Google BigQuery
• Learn how to use pre-built ML APIs on unstructured data and build different kinds of ML models using BigQuery ML.
• Enable instant insights from streaming data
This class is intended for developers who are responsible for:
• Extracting, Loading, Transforming, cleaning, and validating data
• Designing pipelines and architectures for data processing
• Integrating analytics and machine learning capabilities into data pipelines
• Querying datasets, visualizing query results and creating reports
>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<
應用的學習項目
This Specialization 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.
學生職業成果
45%
完成此 專項課程 後開始了新的職業。
可分享的證書
完成後獲得證書
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
需要一些相關領域經驗。需要一些相關經驗。
完成時間大約為3 個月
建議 5 小時/週
英語（English）
字幕：英語（English）, 西班牙語（Spanish）
學生職業成果
45%
完成此 專項課程 後開始了新的職業。
可分享的證書
完成後獲得證書
100% 在線課程
立即開始，按照自己的計劃學習。
靈活的計劃
設置並保持靈活的截止日期。
中級
需要一些相關領域經驗。需要一些相關經驗。
完成時間大約為3 個月
建議 5 小時/週
英語（English）
字幕：英語（English）, 西班牙語（Spanish）
此專項課程包含 5 門課程
Google Cloud Platform Big Data and Machine Learning Fundamentals
11,064 個評分
This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
Modernizing Data Lakes and Data Warehouses with GCP
1,346 個評分
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 Platform 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. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.
Building Batch Data Pipelines on GCP
799 個評分
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 Platform for data transformation including BigQuery, executing Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Cloud Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud Platform using QwikLabs.
Building Resilient Streaming Analytics Systems on GCP
641 個評分
*Note: this is a new course with updated content from what you may have seen in the previous version of this Specialization.
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.
常見問題
退款政策是如何规定的？
如果订阅，您可以获得 7 天免费试听，在此期间，您可以取消课程，无需支付任何罚金。在此之后，我们不会退款，但您可以随时取消订阅。请阅读我们完整的退款政策。
我可以只注册一门课程吗？
可以！点击您感兴趣的课程卡开始注册即可。注册并完成课程后，您可以获得可共享的证书，或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分，系统会自动为您订阅完整的专项课程。访问您的学生面板，跟踪您的进度。
有助学金吗？
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
我可以免费学习课程吗？
完成注册课程后，您可以学习专项课程中的所有课程，并且完成作业后可以获得证书。如果您只想阅读和查看课程内容，可以免费旁听该课程。如果您无法承担课程费用，可以申请助学金。
此课程是 100% 在线学习吗？是否需要现场参加课程？
此课程完全在线学习，无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。
完成专项课程后我会获得大学学分吗？
此专项课程不提供大学学分，但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。
完成专项课程后我会获得大学学分吗？
此专项课程不提供大学学分，但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校，了解详情。Coursera 上的在线学位和 Mastertrack™ 证书提供获得大学学分的机会。
完成专项课程需要多长时间？
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
Do I need to take the courses in a specific order?
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.
What will I be able to do upon completing the Specialization?
Upon completion of this Specialization, you'll have the opportunity to share your information directly with Google and Publicis [more partners coming soon] to be considered for open hiring opportunities. You'll also earn a Specialization Certificate to share with your professional network and potential employers.
Google Cloud Platform is used in a wide variety of environments, all the way from startups to global enterprises. This specialization is designed to help prepare you to implement solutions using Google Cloud Platform in any of these types of environments.
Am I eligible for the Google Cloud Platform free trial?
To be eligible for the free trial, you will need:
- Google account (Google is currently blocked in China)
- Credit card or bank account
- Terms of service
Note: There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602\n\nMore Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
For more details on how the free trial works, visit our documentation page: https://cloud.google.com/free-trial/docs/
What if I have already used up my Google Cloud Platform free trial?
If your current Google account is no longer eligible for the Google Cloud Platform free trial, you can create another Google account. Your new Google account should be used to sign up for the free trial.
How does the free trial work?
View this page for more details: https://cloud.google.com/free-trial/docs/
Is the certificate received after completing a Coursera course or specialization the same as a Google Cloud certification?
No, the certificate received is a Coursera coursework completion certificate and not an official Google Cloud certification. To receive a Google Cloud certification you need to pass a Google Cloud certification exam which must be taken in-person at an official testing center. More information available here: https://cloud.google.com/certification/
I’ve passed all the Coursera courses for the Data Engineering on Google Cloud Platform Specialization. Will I be able to pass the Google Certified Professional Data Engineer certification exam?
Taking courses is a great way to familiarize yourself with the various components of Google Cloud Platform; however, actual real-world, hands-on experience is the best preparation for certification. Combine these courses and work experience and you are on your way to certification.
還有其他問題嗎？請訪問 學生幫助中心。
