This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing. Prerequisites: • Google Cloud Platform Big Data and Machine Learning Fundamentals • Experience using a SQL-like query language to analyze data • Knowledge of either Python or Java Google Account Notes: • Google services are currently unavailable in China.
本课程是 Data Engineering, Big Data, and Machine Learning on GCP 专项课程 专项课程的一部分
Serverless Data Analysis with Google BigQuery and Cloud Dataflow
提供方
教学大纲 - 您将从这门课程中学到什么
周
1完成时间为 7 分钟
Welcome to Serverless Data Analysis with Google BigQuery and Cloud Dataflow
1 个视频 （总计 7 分钟）
1 个视频
完成时间为 5 小时
Module 1: Serverless Data Analysis with BigQuery
19 个视频 （总计 123 分钟）, 4 个测验
19 个视频
What is BigQuery?5分钟
BigQuery Demonstration3分钟
BigQuery Benefits7分钟
BigQuery in a Reference Architecture8分钟
Queries and Functions8分钟
Subqueries and Multiple Tables3分钟
Lab - Serverless Data Analysis (Java/Python) : Part 12分钟
Lab demo and review9分钟
Load and Export Data2分钟
Lab demo and review13分钟
Advanced Capabilities in BigQuery7分钟
Arrays and Structures6分钟
Join condition and Window Functions6分钟
User-defined Functions3分钟
Lab demo and review14分钟
Performance and Pricing7分钟
Wildcard Tables and Partitioning7分钟
BigQuery Plans and Categories4分钟
1 个练习
Module 1 Quiz4分钟
完成时间为 8 小时
Module 2: Autoscaling Data Processing Pipelines with Dataflow
12 个视频 （总计 97 分钟）, 7 个测验
12 个视频
Write Data Pipelines in Java and Python9分钟
Input Output and Run6分钟
Lab demo and review18分钟
MapReduce and Parallel Processing11分钟
GroupBy and Combine7分钟
Combine vs GroupBy7分钟
Lab demo and review6分钟
Side Inputs7分钟
Lab demo and review10分钟
Dataflow Templates and Dataprep4分钟
Resources31
1 个练习
Module 2 Quiz4分钟
4.5
263 个审阅30%
完成这些课程后已开始新的职业生涯
41%
通过此课程获得实实在在的工作福利
24%
加薪或升职
来自Serverless Data Analysis with Google BigQuery and Cloud Dataflow的热门评论
The combination of Java and python is sometimes a bit confusing. Maybe it would be better to split the course in a java and a python version so all the Beam concepts are taught in a single language.
Thanks for designing such a wonderful course outline. I learned valuabe BigQuery and Cloud Dataflow concepts. Best part was to learn how to write data pipelines and execute on cloud using Dataflow.
关于 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.
关于 Data Engineering, Big Data, and Machine Learning on GCP 专项课程
This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems 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 carry out machine learning. The course covers structured, unstructured, and streaming data.
This course teaches the following skills:
• Design and build data processing systems on Google Cloud Platform
• Leverage unstructured data using Spark and ML APIs on Cloud Dataproc
• Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow
• Derive business insights from extremely large datasets using Google BigQuery
• Train, evaluate and predict using machine learning models using Tensorflow and Cloud 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
• Creating and maintaining machine learning and statistical models
• 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 <<<
常见问题
我能否在注册前预览课程？
是的，您可以在注册之前预览第一个视频和查看授课大纲。您必须购买课程，才能访问预览不包括的内容。
我什么时候能够访问课程视频和作业？
如果您决定在班次开始日期之前注册课程，那么您将可以访问课程的所有课程视频和阅读材料。班次开始之后，您便可以提交作业。
我注册之后会得到什么？
在您注册且班次开课之后，您将可以访问所有视频和其他资源，包括阅读材料内容和课程论坛。您将能够查看和提交练习作业，并完成所需的评分作业以获得成绩和课程证书。
我什么时候会收到课程证书？
如果您成功完成课程，您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。
我为什么不能旁听此课程？
该课程是 Coursera 上提供的为数不多的课程之一，目前只对已购买课程或已获得助学金的学生开放。
退款政策是如何规定的？
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