课程信息
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100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

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中级

完成时间大约为8 小时

建议:1 week of study, 6-8 hours/week...

英语(English)

字幕:法语(French), 巴西葡萄牙语, 德语(German), 英语(English), 西班牙语(Spanish), 日语...

您将获得的技能

BigqueryApache BeamDataflowPublish–Subscribe Pattern

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为8 小时

建议:1 week of study, 6-8 hours/week...

英语(English)

字幕:法语(French), 巴西葡萄牙语, 德语(German), 英语(English), 西班牙语(Spanish), 日语...

教学大纲 - 您将从这门课程中学到什么

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

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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

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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
230 个审阅Chevron Right

29%

完成这些课程后已开始新的职业生涯

42%

通过此课程获得实实在在的工作福利

26%

加薪或升职

来自Serverless Data Analysis with Google BigQuery and Cloud Dataflow的热门评论

创建者 ELDec 12th 2018

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.

创建者 MHJun 4th 2018

Nice course. Needed options for python codes in the end of the course. In the beginning you had options to look at both python and java, but this were not the case in the later stages.

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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 <<<...
Data Engineering, Big Data, and Machine Learning on GCP

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