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中級レベル

約11時間で修了

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

英語

字幕:英語

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TensorflowBigqueryGoogle Cloud PlatformCloud Computing

100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

約11時間で修了

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

英語

字幕:英語

シラバス - 本コースの学習内容

1
3時間で修了

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件のビデオ (合計78分), 2 readings, 2 quizzes
13件のビデオ
Introduction to Google Cloud Platform3 分
Compute Power for Analytic and ML Workloads9 分
Demo: Creating a VM on Compute Engine13 分
Elastic Storage with Google Cloud Storage5 分
Build on Google's Global Network3 分
Security: On-premise vs Cloud-native2 分
Evolution of Google Cloud Big Data Tools5 分
Getting Started with Google Cloud Platform and Qwiklabs3 分
Choosing the right approach5 分
What you can do with Google Cloud Platform3 分
Activity: Explore real customer solution architectures7 分
Key roles in a data-driven organization6 分
2件の学習用教材
Google Cloud Public Datasets program10 分
Module Resources10 分
1の練習問題
Module Review5 分
2時間で修了

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件のビデオ (合計50分), 1 reading, 2 quizzes
8件のビデオ
Introduction to machine learning5 分
Challenge: ML for recommending housing rentals8 分
Approach: Move from on-premise to Google Cloud Platform9 分
Demo: From zero to an Apache Spark job in 10 minutes or less6 分
Challenge: Utilizing and tuning on-premise clusters6 分
Move storage off-cluster with Google Cloud Storage4 分
Lab Intro2 分
1件の学習用教材
Module Resources5 分
1の練習問題
Module Review15 分
3時間で修了

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件のビデオ (合計74分), 2 readings, 2 quizzes
13件のビデオ
Demo: Query 2 billion lines of Github code in less than 30 seconds11 分
BigQuery: Fast SQL Engine4 分
Demo: Exploring bike share data with SQL11 分
Data quality4 分
BigQuery managed storage5 分
Insights from geographic data2 分
Demo: Analyzing lightning strikes with BigQuery GIS7 分
Choosing a ML model type for structured data4 分
Predicting customer lifetime value5 分
BigQueryML: Create models with SQL3 分
Phases in ML model lifecycle2 分
BigQuery ML: key features walkthrough5 分
2件の学習用教材
Lab Intro10 分
Module Resources10 分
1の練習問題
Module Review4 分
2
2時間で修了

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件のビデオ (合計31分), 1 reading, 2 quizzes
8件のビデオ
Message-oriented architectures with Cloud Pub/Sub6 分
Designing streaming pipelines with Apache Beam3 分
Implementing streaming pipelines on Cloud Dataflow3 分
Visualizing insights with Data Studio3 分
Creating charts with Data Studio2 分
Demo: Data Studio walkthrough7 分
Lab Intro1 分
1件の学習用教材
Module Resources10 分
1の練習問題
Module Review4 分
2時間で修了

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件のビデオ (合計55分), 2 readings, 2 quizzes
10件のビデオ
How does ML on unstructured data work?3 分
Demo: ML built into Google Photos1 分
Comparing approaches to ML2 分
Demo: Using ML building blocks7 分
Using pre-built AI to create a chatbot4 分
Customizing Pre-built models with AutoML7 分
Lab Intro22
Building a Custom Model1 分
Demo: Text classification done three ways21 分
2件の学習用教材
Additional resources to build custom models10 分
Module Resources10 分
1の練習問題
Module Review
5分で修了

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件のビデオ (合計5分)
1件のビデオ
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1,045件のレビューChevron Right

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人気のレビュー

by 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.

by 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.

Google Cloudについて

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....

Data Engineering on Google Cloud Platformの専門講座について

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 on Google Cloud Platform

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  • 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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