Perform Foundational Data, ML, and AI Tasks in Google Cloud: Challenge Lab 1 hour 20 minutes 9 Credits Rate Lab GSP323 Google Cloud Self-Paced Labs
Overview In a challenge lab you’re given a scenario and a set of tasks. Instead of following step-by-step instructions, you will use the skills learned from the labs in the quest to figure out how to complete the tasks on your own! An automated scoring system (shown on this page) will provide feedback on whether you have completed your tasks correctly.
When you take a challenge lab, you will not be taught new Google Cloud concepts. You are expected to extend your learned skills, like changing default values and reading and researching error messages to fix your own mistakes.
To score 100% you must successfully complete all tasks within the time period!
This lab is recommended for students who have enrolled in the Perform Foundational Data, ML, and AI Tasks in Google Cloud quest. Are you ready for the challenge?
Topics tested:
Create a simple Dataproc job Create a simple DataFlow job Create a simple Dataprep job Perform one of the three Google machine learning backed API tasks Setup Before you click the Start Lab button Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources will be made available to you.
This Qwiklabs hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.
What you need To complete this lab, you need:
Access to a standard internet browser (Chrome browser recommended). Time to complete the lab. Note: If you already have your own personal Google Cloud account or project, do not use it for this lab.
Note: If you are using a Pixelbook, open an Incognito window to run this lab.
How to start your lab and sign in to the Google Cloud Console Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is a panel populated with the temporary credentials that you must use for this lab.
Open Google Console
Copy the username, and then click Open Google Console. The lab spins up resources, and then opens another tab that shows the Sign in page.
Sign in
Tip: Open the tabs in separate windows, side-by-side.
If you see the Choose an account page, click Use Another Account. Choose an account In the Sign in page, paste the username that you copied from the Connection Details panel. Then copy and paste the password.
Important: You must use the credentials from the Connection Details panel. Do not use your Qwiklabs credentials. If you have your own Google Cloud account, do not use it for this lab (avoids incurring charges).
Click through the subsequent pages:
Accept the terms and conditions. Do not add recovery options or two-factor authentication (because this is a temporary account). Do not sign up for free trials. After a few moments, the Cloud Console opens in this tab.
Note: You can view the menu with a list of Google Cloud Products and Services by clicking the Navigation menu at the top-left. Cloud Console Menu Challenge scenario As a junior data engineer in Jooli Inc. and recently trained with Google Cloud and a number of data services you have been asked to demonstrate your newly learned skills. The team has asked you to complete the following tasks.
You are expected to have the skills and knowledge for these tasks so don’t expect step-by-step guides.
Task 1: Run a simple Dataflow job You have used Dataflow in the question to load data into BigQuery from Pub/Sub, now use the Dataflow batch template Text Files on Cloud Storage to BigQuery under "Process Data in Bulk (batch)" to transfer data from a Cloud Storage bucket (gs://cloud-training/gsp323/lab.csv). The following table has the values you need to correctly configure the Dataflow job.
You will need to make sure you have:
created a BigQuery dataset called lab replace YOUR_PROJECT with the lab project name created a Cloud Storage Bucket called YOUR_PROJECT Field Value JavaScript UDF path in Cloud Storage gs://cloud-training/gsp323/lab.js JSON path gs://cloud-training/gsp323/lab.schema JavaScript UDF name transform BigQuery output table YOUR_PROJECT:lab.customers Cloud Storage input path gs://cloud-training/gsp323/lab.csv Temporary BigQuery directory gs://YOUR_PROJECT/bigquery_temp Temporary location gs://YOUR_PROJECT/temp Wait for the job to finish before trying to check your progress.
Click Check my progress to verify the objective. Data successfully loaded into BigQuery
If you don't get a green check mark, click on the Score fly-out on the top right and click Check my progress on the relevant step. A hint pop up opens to give you advice. Task 2: Run a simple Dataproc job You have used Dataproc in the quest, now you must run another example Spark job using Dataproc.
Before you run the job, log into one of the cluster nodes and copy the /data.txt file into hdfs (use the command hdfs dfs -cp gs://cloud-training/gsp323/data.txt /data.txt).
Run a Dataproc job using the values below.
Field Value Region us-central1 Job type Spark Main class or jar org.apache.spark.examples.SparkPageRank Jar files file:///usr/lib/spark/examples/jars/spark-examples.jar Arguments /data.txt Max restarts per hour 1 Wait for the job to finish before trying to check your progress.
Click Check my progress to verify the objective. Spark job run successfully
If you don't get a green check mark, click on the Score fly-out on the top right and click Check my progress on the relevant step. A hint pop up opens to give you advice. Task 3: Run a simple Dataprep job You have used Dataprep to import data files and transformed them to gain views of the data. Use Dataprep to import one CSV file (described below) that holds data of lab executions.
gs://cloud-training/gsp323/runs.csv structure:
runid userid labid lab_title start end time score state 5556 545 122 Lab 122 2020-04-09 16:18:19 2020-04-09 17:10:11 3112 61.25 SUCCESS 5557 116 165 Lab 165 2020-04-09 16:44:45 2020-04-09 18:13:58 5353 60.5 SUCCESS 5558 969 31 Lab 31 2020-04-09 17:59:01 2020-04-09 18:02:09 188 0 FAILURE Perform the following transforms to ensure the data is in the right state:
Remove all rows with the state of "FAILURE" Remove all rows with 0 or 0.0 as a score (Use the regex pattern /(^0$|^0.0$)/) Label columns with the names above Make sure you run the job. You will need to wait until the Dataflow job completes before you can grade this task.
Click Check my progress to verify the objective. Dataprep job completed
If you don't get a green check mark, click on the Score fly-out on the top right and click Check my progress on the relevant step. A hint pop up opens to give you advice. Task 4: AI Complete one of the tasks below, YOUR_PROJECT must be replaced with your lab project name.
Use Google Cloud Speech API to analyze the audio file gs://cloud-training/gsp323/task4.flac. Once you have analyzed the file you can upload the resulting analysis to gs://YOUR_PROJECT-marking/task4-gcs.result.
Use the Cloud Natural Language API to analyze the sentence from text about Odin. The text you need to analyze is "Old Norse texts portray Odin as one-eyed and long-bearded, frequently wielding a spear named Gungnir and wearing a cloak and a broad hat." Once you have analyzed the text you can upload the resulting analysis to gs://YOUR_PROJECT-marking/task4-cnl.result.
Use Google Video Intelligence and detect all text on the video gs://spls/gsp154/video/train.mp4. Once you have completed the processing of the video, pipe the output into a file and upload to gs://YOUR_PROJECT-marking/task4-gvi.result. Ensure the progress of the operation is complete and the service account you're uploading the output with has the Storage Object Admin role.
Click Check my progress to verify the objective. One of the tasks successfully completed.
If you don't get a green check mark, click on the Score fly-out on the top right and click Check my progress on the relevant step. A hint pop up opens to give you advice.
Congratulations!