This 1-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.
At the end of this course, participants will be able to:
• Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
• Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform
• Employ BigQuery and Cloud Datalab to carry out interactive data analysis
• Choose between Cloud SQL, BigTable and Datastore
• Train and use a neural network using TensorFlow
• Choose between different data processing products on the Google Cloud Platform
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
Google Account Notes:
• Google services are currently unavailable in China.
本課程是 Data Engineering on Google Cloud Platform 專項課程 專項課程的一部分
Google Cloud Platform Big Data and Machine Learning Fundamentals
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1完成時間為 3 小時
Introduction to the Data and Machine Learning on Google Cloud Platform Specialization
Welcome to the Big Data and Machine Learning fundamentals on GCP course. Here you will learn the basics of how the course is structured and the four main big data challenges you will solve for.
13 個視頻 （總計 78 分鐘）, 2 個閱讀材料, 2 個測驗
13 個視頻
Introduction to Google Cloud Platform3分鐘
Compute Power for Analytic and ML Workloads9分鐘
Demo: Creating a VM on Compute Engine13分鐘
Elastic Storage with Google Cloud Storage5分鐘
Build on Google's Global Network3分鐘
Security: On-premise vs Cloud-native2分鐘
Evolution of Google Cloud Big Data Tools5分鐘
Getting Started with Google Cloud Platform and Qwiklabs3分鐘
Choosing the right approach5分鐘
What you can do with Google Cloud Platform3分鐘
Activity: Explore real customer solution architectures7分鐘
Key roles in a data-driven organization6分鐘
2 個閱讀材料
Google Cloud Public Datasets program10分鐘
Module Resources10分鐘
1 個練習
Module Review5分鐘
完成時間為 2 小時
Recommending Products using Cloud SQL and Spark
In this module you will have an existing Apache SparkML recommendation model that is running on-premise. You will learn about recommendation models and how you can run them in the cloud with Cloud Dataproc and Cloud SQL.
8 個視頻 （總計 50 分鐘）, 1 個閱讀材料, 2 個測驗
8 個視頻
Introduction to machine learning5分鐘
Challenge: ML for recommending housing rentals8分鐘
Approach: Move from on-premise to Google Cloud Platform9分鐘
Demo: From zero to an Apache Spark job in 10 minutes or less6分鐘
Challenge: Utilizing and tuning on-premise clusters6分鐘
Move storage off-cluster with Google Cloud Storage4分鐘
Lab Intro2分鐘
1 個閱讀材料
Module Resources5分鐘
1 個練習
Module Review15分鐘
完成時間為 3 小時
Predict Visitor Purchases with BigQuery ML
In this module, you will learn the foundations of BigQuery and big data analysis at scale. You will then learn how to build your own custom machine learning model to predict visitor purchases using just SQL with BigQuery ML.
13 個視頻 （總計 74 分鐘）, 2 個閱讀材料, 2 個測驗
13 個視頻
Demo: Query 2 billion lines of Github code in less than 30 seconds11分鐘
BigQuery: Fast SQL Engine4分鐘
Demo: Exploring bike share data with SQL11分鐘
Data quality4分鐘
BigQuery managed storage5分鐘
Insights from geographic data2分鐘
Demo: Analyzing lightning strikes with BigQuery GIS7分鐘
Choosing a ML model type for structured data4分鐘
Predicting customer lifetime value5分鐘
BigQueryML: Create models with SQL3分鐘
Phases in ML model lifecycle2分鐘
BigQuery ML: key features walkthrough5分鐘
2 個閱讀材料
Lab Intro10分鐘
Module Resources10分鐘
1 個練習
Module Review4分鐘
週
2完成時間為 2 小時
Create Streaming Data Pipelines with Cloud Pub/sub and Cloud Dataflow
In this module you will engineer and build an auto-scaling streaming data pipeline to ingest, process, and visualize data on a dashboard. Before you build your pipeline you'll learn the foundations of message-oriented architecture and pitfalls to avoid when designing and implementing modern data pipelines.
8 個視頻 （總計 31 分鐘）, 1 個閱讀材料, 2 個測驗
8 個視頻
Message-oriented architectures with Cloud Pub/Sub6分鐘
Designing streaming pipelines with Apache Beam3分鐘
Implementing streaming pipelines on Cloud Dataflow3分鐘
Visualizing insights with Data Studio3分鐘
Creating charts with Data Studio2分鐘
Demo: Data Studio walkthrough7分鐘
Lab Intro1分鐘
1 個閱讀材料
Module Resources10分鐘
1 個練習
Module Review4分鐘
完成時間為 2 小時
Classify Images with Pre-Built Models using Vision API and Cloud AutoML
Don't want to create a custom ML model from scratch? Learn how to leverage and extend pre-built ML models like the Vision API and Cloud AutoML for image classification.
10 個視頻 （總計 55 分鐘）, 2 個閱讀材料, 2 個測驗
10 個視頻
How does ML on unstructured data work?3分鐘
Demo: ML built into Google Photos1分鐘
Comparing approaches to ML2分鐘
Demo: Using ML building blocks7分鐘
Using pre-built AI to create a chatbot4分鐘
Customizing Pre-built models with AutoML7分鐘
Lab Intro22
Building a Custom Model1分鐘
Demo: Text classification done three ways21分鐘
2 個閱讀材料
Additional resources to build custom models10分鐘
Module Resources10分鐘
1 個練習
Module Review
完成時間為 5 分鐘
Summary
In this final module, we will review the key challenges, solutions, and topics covered as part of this fundamentals course. We will also review additional resources and the steps you can take to get certified as a Google Cloud Data Engineer.
1 個視頻 （總計 5 分鐘）
1 個視頻
4.6
1,031 個審閱47%
完成這些課程後已開始新的職業生涯
43%
通過此課程獲得實實在在的工作福利
熱門審閱
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.
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.
關於 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.
關於 Data Engineering on Google Cloud Platform 專項課程
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 <<<
常見問題
我什么时候能够访问课程视频和作业？
注册以便获得证书后，您将有权访问所有视频、测验和编程作业（如果适用）。只有在您的班次开课之后，才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程，可能无法访问某些作业。
我订阅此专项课程后会得到什么？
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。
退款政策是如何规定的？
有助学金吗？
Are there prerequisites for this course?
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
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
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/
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 this course similar to CPB100?
Yes, this online course is based on the instructor-led training formerly known as CPB100.
Does this course relate to the Google Certified Professional Data Engineer certification?
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/
What is a Google certification?
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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