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Engineer Data in Google Cloud

Advanced 7단계 8시간 크레딧 51개

This advanced-level quest is unique amongst the other Qwiklabs offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From BigQuery, to Dataprep, to Cloud Composer & Tensorflow, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Complete this quest, including the the challenge lab at the end, to receive an exclusive Google Cloud digital badge. The challenge lab does not provide prescriptive steps, but require solutions to be built with minimal guidance and will put your Google Cloud technology skills to the test!

Data Machine Learning Business Transformation

기본 요건:

This Quest requires proficiency with Google Cloud Services, particularly those relating to working with large datasets. It is recommended that the student have at least earned a Badge by completing the hands-on labs in the Baseline: Data, ML, and AI and/or the Google Cloud Essentials Quests before beginning. Additional lab experience with the Scientific Data Processing and the Machine Learning APIs Quests will be useful.

Quest Outline

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Creating a Data Transformation Pipeline with Cloud Dataprep

Cloud Dataprep by Trifacta is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis. In this lab you will explore the Cloud Dataprep UI to build a data transformation pipeline.

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Building an IoT Analytics Pipeline on Google Cloud

This lab shows you how to connect and manage devices using Cloud IoT Core; ingest the stream of information using Cloud Pub/Sub; process the IoT data using Cloud Dataflow; use BigQuery to analyze the IoT data. Watch this short video, Easily Build an IoT Analytics Pipeline.

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ETL Processing on Google Cloud Using Dataflow and BigQuery

In this lab you will build several Data Pipelines that will ingest data from a publicly available dataset into BigQuery.

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Predict Visitor Purchases with a Classification Model in BQML

In this lab you will use a newly available ecommerce dataset to run some typical queries that businesses would want to know about their customers’ purchasing habits.

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Predict Housing Prices with Tensorflow and AI Platform

In this lab you will build an end to end machine learning solution using Tensorflow + AI Platform and leverage the cloud for distributed training and online prediction.

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Cloud Composer: Copying BigQuery Tables Across Different Locations

In this advanced lab you will create and run an Apache Airflow workflow in Cloud Composer that exports tables from a BigQuery dataset located in Cloud Storage bucktes in the US to buckets in Europe, then import th0se tables to a BigQuery dataset in Europe.

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Engineer Data in Google Cloud: Challenge Lab

This challenge lab tests your skills and knowledge from the labs in the Engineer Data in Google Cloud quest. You should be familiar with the content of labs before attempting this lab.

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