Data Engineering
9 Labs · 49 Credits · 7h 5m
Cert Exam Practice
This Quest is intended to provide hands-on practice for those preparing for the Google Cloud Certified Professional Data Engineer Certification. Students will get hands-on exposure to a wide range of Google Cloud Services and techniques which are closely mapped to the topic areas in the certification test. Be aware that while practice with these labs will increase your knowledge and abilities in these topic areas, you will need other preparation to succeed in the question and answer test itself (such as work experience).
Weather Data in BigQuery
In this lab you analyze historical weather observations using BigQuery and use weather data in conjunction with other datasets. This lab is part of a series of labs on processing scientific data.
fundamental
5 Credits
35 Minutes
Analyzing Natality Data Using Datalab and BigQuery
In this lab you analyze a large (137 million rows) natality dataset using Google BigQuery and Cloud Datalab. This lab is part of a series of labs on processing scientific data.
advanced
7 Credits
30 Minutes
Predicting Baby Weight with TensorFlow on Cloud ML Engine
In this lab you train, evaluate, and deploy a machine learning model to predict a baby’s weight. You then send requests to the model to make online predictions. This lab is part of a series of labs on processing scientific data.
expert
9 Credits
1 Hour 30 Minutes
Bigtable: Qwik Start - Hbase Shell
This hands-on lab will show you how to use the HBase shell to connect to a Cloud Bigtable instance.
introductory
1 Credit
30 Minutes
Run a Big Data Text Processing Pipeline in Cloud Dataflow
In this lab you will use Google Cloud Dataflow to create a Maven project with the Cloud Dataflow SDK, and run a distributed word count pipeline using the Google Cloud Platform Console.
advanced
7 Credits
40 Minutes
Dataproc: Qwik Start - Console
This page shows you how to use the Google Cloud Platform Console to create a Google Cloud Dataproc cluster, run a simple Apache Spark job in the cluster, then modify the number of workers in the cluster.
introductory
1 Credit
30 Minutes
Building an IoT Analytics Pipeline on Google Cloud Platform
This lab shows you how to connect and manage devices using Cloud IoT Core; ingest the steam of information using Cloud Pub/Sub; process the IoT data using Cloud Dataflow; use BigQuery to analyze the IoT data.
advanced
7 Credits
50 Minutes
Working with Google Cloud Dataprep
Cloud Dataprep is Google's self-service data preparation tool. In this lab, you will learn how to use Cloud Dataprep to clean and enrich multiple datasets using a mock use case scenario of customer info and purchase history.
fundamental
5 Credits
1 Hour
Classify Text into Categories with the Natural Language API
In this lab you’ll learn how to classify text into categories using the Natural Language API
advanced
7 Credits
1 Hour