The business value of AI is projected to reach $1.2 trillion this year according to Gartner. Yet 40% of enterprise companies are not adopting AI. Why not?
3 simple reasons:
- Data Scientists are hard to find and hire. Want to become one? There’s a lab for that. Enroll in the Data Science on GCP quest by Friday, October 12th and you’ll get 40 credits (free of charge, no CC required). The labs in this quest are derived from the book Data Science on Google Cloud Platform.
- Data analysts with SQL skills (and other programming languages) are also rare. Get practice running SQL queries in the BigQuery console in the Introduction to SQL for BigQuery and Cloud SQL lab. Then experiment with SQL and ML in the Ingest data into the Cloud Using Google App Engine lab. You’ll run Python scripts to download, automatically fetch, and clean data using Google App Engine. You’ll also create a new application and deploy it to the Google App Engine:
Then use a Flask framework to ingest data and invoke it using cron:3. Infrastructure AI is resource-intensive, in terms of both staff, and compute power. Many on-prem setups simply cannot handle the demands of AI. You can learn to take advantage of Google Cloud’s compute power to run your advanced AI jobs. The Google Cloud Dataflow to process data lab shows you how to configure BigQuery and install Python packages to use Apache Beam:
Then you will monitor the progress of your Cloud Dataflow job and inspect the processed data:
Need more practice with the GCP infrastructure? Visualize data with Google Data Studio by running the query to get the IP address to connect to the Cloud SQL:
Then create table views to look at flights that are delayed by 10, 15, 20 minutes:
After connecting with the Data Studio, you’ll create a data visualization for flight delays:
Tackle the quest to practice ingestion, preparation, processing, querying, exploring and visualizing of data sets using GCP. When you earn the badge, let us know. You can find us at @Qwiklabs – and we’re always happy to hear about your accomplishments!
How do you learn something new? Do you read a book, watch a video, take a course? Maybe the right answer is poetry.
When you’re learning to use data science tools you need, well, big data to practice. And that’s where Shakespeare comes in. Billy S. wrote 37 plays, 154 sonnets and invented 1700 words (like eyeball, bedazzled, and arch-villain). His works are publicly available and perfect for data manipulation. With the help of Shakespeare, learn how data science tools like BigQuery and TensorFlow can help you take advantage of powerful Google Cloud machine learning technology. And for a limited time, use the links below and get 37 free Qwiklabs credits (as many credits as plays) to take the bard’s favorite labs.
– BigQuery: Qwik Start – Command Line: Storing and querying massive datasets can be expensive. Learn how Google Cloud can help you save, after all, “if money go before, all ways do lie open” (The Merry Wives of Windsor). Learn how to move your data into BigQuery and take advantage of the processing power of Google’s infrastructure.
– Big Data Analysis to Slide Presentation: Did you know that Shakespeare invented the word “manager”? Impress yours by learning how to gather and crunch your data, then generate a slide and spreadsheet presentation to blow away management and stakeholders with your breathtaking analytical capabilities and intelligent conclusions.
– Run a Big Data Text Processing Pipeline in Cloud Dataflow: Learn how to run a Dataflow pipeline that counts the occurrences of unique words in a text file. Not only will you learn how many times the word “alas” appears in King Lear, you’ll learn to use a powerful tool for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation.
– TensorFlow For Poets: Finally, while we don’t know if a rose by any other name smells as sweet, we can use TensorFlow to identify a rose among a floral lineup. Think about what else you could use this technology for – scanning for free parking spaces? Locating your company’s discarded scooters?
Have you heard of IIoT, Industrial Internet of Things? Enterprise companies are discovering and experimenting with IoT in industries from manufacturing to energy to automobiles. As companies recognize more consumer and industrial uses for IoT, demand for IoT expertise is rising.
Set yourself apart by earning the new Google Cloud IoT badge. Click the link below to enroll by Friday, October 12, and you will get a free 30-day pass to the entire Qwiklabs lab catalog, including the new IoT labs. Think you can earn the badge in 30 days?
You get 8 labs to help you learn about Google Cloud’s IoT Core service and its integration with other services like GCS, Dataprep, Stackdriver and Firestore. Use simulator code to mimic IoT devices, then use what you learn to implement the same streaming pipeline with real world IoT devices. Here’s some of what you will do:
Complete all 8 labs and add the IoT on Google Cloud badge to your resume. Good luck!
Interested in self-driving cars? Learn the technology behind the magic – then sit back, relax, and let the car do it for you.
- How do autonomous cars recognize speed limit signs? “See” for yourself with the Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API lab (bonus, follow that link and get the lab free of charge). You’ll build a model that recognizes landmarks and items in photos with a simple REST API.
- Then, how do cars know the speed limit? The Extract, Analyze, and Translate Text from Images with the Cloud ML APIs lab shows you how to translate signs – not just read them – which means machine learning can improve your commute no matter what side of the road you drive on.
- Some cars know what’s around you – trucks, cars, motorcycles, even reindeer. Learn how to use Google’s Machine Learning tools to Classify Images of Clouds in the Cloud with AutoML Vision.
- Even when conditions aren’t perfect, cars can predict what’s next. Start making predictions with the Cloud ML Engine: Qwik Start lab.
With these labs, you’re well on your way to your next badge, Machine Learning APIs. Enroll here, and you’ll get 55 Qwiklabs credits to start your next Quest (limited offer, ends Friday, Sept. 21).
Good luck, buckle up!
Infrastructure Architect is the fourth highest-paying job in the tech industry. Add the Cloud Architecture Quest badge to your resume and set your sights on the Cloud ACE certification (and maybe one of the 1,097 open architect jobs). The Quest maps to the topics covered in the new ACE certification exam guide and puts your GCP knowledge to test. Here’s how:
- In the Cloud IAM: Qwik Start lab you’ll assign a role to a second user and remove assigned roles associated with Identity and Access Management (IAM). This maps to section 5 from the exam guide, Configuring Access and Security.
Explore the IAM console in the lab and you’ll see:
- Practice creating Google Compute Engine VM instance in the Stackdriver: Qwik Start lab. It will help you with section 3.1 from the exam guide, deploying and implementing Compute Engine resources.
- Tackle the Orchestrating the Cloud with Kubernetes lab to provision a Kubernetes cluster and deploy and manage Docker containers using kubectl. This helps you practice for section 3.2, Deploying and implementing Kubernetes Engine resources.
Here’s a brain teaser! Nginx container is running, expose it using kubectl expose command in the lab.
What happened? Share your results @Qwiklabs
- Conquer the Deployment Manager – Full Production lab to set up black box monitoring with Stackdriver Dashboard and establish uptime check alerts to trigger incident responses. This maps to section 3.7 from the exam guide, Deploying an Application using Deployment Manager.
Why wait? Enroll in the Cloud Architecture Quest by Friday, August 24th and get a 1-month pass to help you prepare for the Associate Cloud Engineer Certification exam.
What kind of cloud is this?
I don’t know either. Can you think of other types of images that would be useful to classify? For example, if you have an online tire shop, wouldn’t it be cool if your customers could upload a photo of their current tire to find a matching replacement?
AutoML can help your tire shop decrease the number of returns and increase customer delight. And it’s easier than you think – learn how to take advantage of this powerful new tool with a new lab, AutoML Vision API.
Here’s some of what you’ll do:
- You’ll be prompted to log into the AutoML UI. Open the link in a new tab to make it easy to hop between AutoML and your lab manual. Then, you’ll log into AutoML with your Qwiklabs-provided credentials.
- In the AutoML UI, you will see a button for “Billing”. You do not need to worry about billing for this lab, as Qwiklabs covers the cost of this lab for you.
- When you load data into your storage bucket, you’ll set your project name with one of the first commands you run. Find your project name on the left of your lab manual, just below your GCP credentials:
AutoML is currently in beta, so we expect to see constant changes to the user interface. Send any questions to Support@Qwiklabs.com and we’ll be happy to help. Plus you’ll help us keep the lab up to date as the product continues to improve!
Curious about what type of clouds were spotted during our trip to Muir Woods? Here are our model’s predictions:
The model is 99% certain these are cumulus clouds! Prediction certainty and accuracy would be better if we trained our model with more than 20 images per category. When you’re helping customers order tires, you will probably want to use 100+ photos per category.
Big things are happening in Google Cloud. BigQuery ML, for example, just announced at Next ‘18. Even if you weren’t there, you can still take advantage of 33+ new labs released at the conference. And if you haven’t yet seen the new BigQuery interface, you can check it out with a lab.
Here’s what’s new on Qwiklabs:
- Predict Visitor Purchases with a Classification Model in BQML: Use the latest and greatest technology to answer the top question in online retail. Click here to take the lab free of charge, first 25 readers only.
- Classify Images of Clouds in the Cloud with AutoML Vision: AutoML Vision helps developers with limited ML expertise train high quality image recognition models. Take AutoML on a test drive with this lab.
- Managing Cloud Infrastructure with Terraform: #MakeGoogleDoIt – launch your cloud resources, that is. Learn how Terraform can boost your team’s efficiency, by creating configuration files that can be shared, treated as code, edited, reviewed, and versioned.
- Kubernetes Solutions: Work hard, play harder. Use Kubernetes to run dedicated gaming servers, plus 7 more advanced Kubernetes use cases in this Quest.
- Network Performance and Optimization: If you’re the one they call when the network is down, these labs are for you. Learn how GCP can help you sleep at night with better network speed, performance, and reliability.
- Challenge Quest: Your company is ready to launch a brand new website, but the person who built the new site left the company before they could deploy it. Your challenge is to deploy the site in the public cloud. This and six other scenarios make up the Challenge Quest, to test your skills in a simulated crisis. Good luck!
If you have an Advantage subscription, all of this new content is included in your subscription, no extra charge. Not a subscriber yet? Use promo code NEW33 for 33% off your first month. Promo code is valid through August 1o (Friday).
Good luck on your next Quest!