课程信息
4.6
5,278 个评分
968 个审阅

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11 小时

建议:1 week of study, 6-10 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

TensorflowBigqueryGoogle Cloud PlatformCloud Computing

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11 小时

建议:1 week of study, 6-10 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 14 分钟

Introduction to the Data and Machine Learning on Google Cloud Platform Specialization

...
4 个视频 (总计 13 分钟), 1 个阅读材料
4 个视频
Course Overview and Agenda5分钟
Getting Started with Google Cloud Platform and Qwiklabs2分钟
Meet Your Instructor3分钟
1 个阅读材料
Please read me1分钟
完成时间为 1 小时

Introduction to Google Cloud Platform and its Big Data Products

In this module you will be introduced to Google Cloud Platform and the data handling aspects of the platform....
5 个视频 (总计 31 分钟), 1 个测验
5 个视频
What is the Google Cloud Platform?14分钟
GCP Big Data Products9分钟
Usage Scenarios5分钟
Module Resources27
1 个练习
Module Review2分钟
完成时间为 4 小时

Foundations of GCP Compute and Storage

In this module, we introduce the foundations of the Google Cloud Platform: compute and storage and introduce how they work to provide data ingest, storage, and federated analysis....
9 个视频 (总计 54 分钟), 1 个阅读材料, 3 个测验
9 个视频
CPUs On Demand7分钟
Lab Overview37
Lab Review8分钟
A Global Filesystem14分钟
Lab Overview1分钟
Lab Review14分钟
Module Review3分钟
Module Resources3分钟
1 个阅读材料
Module Resources10分钟
1 个练习
Module Review4分钟
完成时间为 4 小时

Data Analysis on the Cloud

In this module we introduce the common Big Data use cases that Google will manage for you. These are the things that are widely done in industry today and for which we provide easy migration to the cloud....
10 个视频 (总计 90 分钟), 3 个测验
10 个视频
Stepping Stones to Transformation20分钟
Your SQL Database in the Cloud5分钟
Lab Overview24
Lab Review22分钟
Managed Hadoop in the Cloud8分钟
Lab Overview17
Lab Review27分钟
Module Review3分钟
Module Resources1分钟
1 个练习
Module Review4分钟
完成时间为 5 小时

Scaling Data Analysis and Machine Learning

This module is about the more transformational technologies in Google Cloud platform that may not have immediate parallels to technologies that attendees are using (“what's next”)....
21 个视频 (总计 82 分钟), 1 个阅读材料, 4 个测验
21 个视频
Fast Random Access11分钟
Warehouse and Interactively Query Petabytes with Google BigQuery3分钟
Ingesting data into BigQuery2分钟
Interactive, Iterative Development with Cloud Datalab1分钟
Cloud Datalab : Demo3分钟
Datalab supports BigQuery2分钟
Lab Overview27
Lab Review : Setting up Datalab5分钟
Lab Review : Working in ipython notebook6分钟
Introduction25
Machine Learning with TensorFlow8分钟
Training and creating a Neural Network Model : Part 11分钟
Training and Creating a Neural Network Model : Part 25分钟
Lab Overview4分钟
Pre-built Machine Learning Models4分钟
Pre-built ML APIs : Examples8分钟
Lab Review8分钟
Module Review2分钟
Scaling Data Analysis : Resources10
Machine Learning : Resources14
1 个阅读材料
Scaling Data Analysis : Resources1分钟
1 个练习
Module Review18分钟
完成时间为 18 分钟

Data Processing Architectures: Scalable Ingest, Transform and Load

In this module we will introduce you to data processing architectures in Google Cloud Platform: Asynchronous processing with TaskQueues. Message-oriented architectures with Pub/Sub. Creating pipelines with Dataflow....
4 个视频 (总计 9 分钟), 1 个阅读材料, 1 个测验
4 个视频
Message-oriented Architectures3分钟
Serverless Data Pipelines3分钟
Module Review32
1 个阅读材料
Module Resources5分钟
1 个练习
Module Review4分钟
完成时间为 15 分钟

Summary of GCP, Big Data and ML

...
3 个视频 (总计 5 分钟), 1 个阅读材料
3 个视频
Next Steps1分钟
Additional Resources35
1 个阅读材料
Additional Resources10分钟
4.6
968 个审阅Chevron Right

48%

完成这些课程后已开始新的职业生涯

44%

通过此课程获得实实在在的工作福利

热门审阅

创建者 VSMar 3rd 2019

Overall a good curated course to help understand the GCP offerings and high level architecture of how their offerings fit in the current landscape. Easy to follow along as this was fundamental course.

创建者 CRDec 27th 2017

This was a great course to understand at a high level how to design and create my data ecosystem and how to do it sustainably. Hopefully, next courses provide more in-depth the technical features.

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 on Google Cloud Platform 专项课程

>>>Look for details below for COMPLETION CHALLENGE, receive up to $150 in Qwiklabs credits<<< This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. Looking to make a career change? 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. 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 COMPLETION CHALLENGE For every course you complete before May 5, 2019, we will send you 30 Qwiklabs credits (upto $150 USD value)! >>> 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 on Google Cloud Platform

常见问题

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  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。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。如果您只想阅读和查看课程内容,可以免费旁听课程。

  • Before enrolling in this course, participants should have roughly 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

  • 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

    More 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/

  • 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.

  • View this page for more details: https://cloud.google.com/free-trial/docs/

  • Yes, this online course is based on the instructor-led training formerly known as CPB100.

  • The course covers the topics presented on the certification exam, however we recommend additional preparation including hands-on product experience. The best preparation for certification is real-world, hands-on experience. Review the Google Certified Professional Data Engineer certification preparation guide for further information and resources at https://cloud.google.com/certification/guides/data-engineer/

  • Google’s Certification Program gives customers and partners a way to demonstrate their technical skills in a particular job-role and technology. Individuals are assessed using a variety of rigorously developed industry-standard methods to determine whether they meet Google’s proficiency standards. Read more at https://cloud.google.com/certification/

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