Get started with Google Cloud APIs

83% of enterprise workloads will be in the cloud by 2020. How? API integration! Want to get started with cloud APIs? Qwiklabs can help. Take any of the labs below and you’ll get 10 Qwiklabs credits by November 21st (free of charge, no CC required).

  1. Introduce yourself to Google Cloud APIs and understand key principles of API communication, architecture and authentication.

For example, you’ll work with Cloud Storage API methods to inspect the Fitness API and monitor traffic levels, error rates and latencies in the Dashboard:

Then, you’ll work with authentication services with Google Cloud APIs. For example, to access user data, you’ll authenticate JSON/REST API by using OAuth 2.0 playground.

2. Got a picture of your pet? Analyze an image with the APIs Explorer: Qwik Start lab. You’ll create a Cloud Storage bucket, upload an image to the bucket. You can use an image of a good dog, Bailey (:

You’ll then call the Cloud Vision API to analyze the image. When you’re done, your request field will look similar to this:

Does it? Share your results @Qwiklabs.

3. How far have you memorized the value of pi? Put Google Cloud to the test. Create a cluster using Cloud Dataproc API and then run a Apache Spark job to calculate an approximate value of pi in that cluster.

Two workers aren’t enough for data intensive processes like these. Add 3 more workers to update the cluster with Dataproc API:

Have you verified the update? How many worker nodes do you see? Share your results @Qwiklabs.

Take the labs and don’t forget you’ll get 10 Qwiklabs credits (free of charge, no CC required).

 

Cloud training tricks & treats

It was a dark and stormy night. The power flickers, then goes out. Oh no, all of your servers in the next room are off! Your business is down until further notice!

Sound scary? We can help. Whether you’re moving from on-premise to the cloud or looking to build your cloud skills to make your next career move, learn how the public cloud can help you vanquish the monster in your closet with Google Cloud labs. And your Halloween treat? Click here to take the “happy Halloween” lab and you’ll get candy – wait – Qwiklabs credits (30 of them) – enough to take up to 10 labs free of charge. Hurry, offer ends at midnight (on November 2)!

Use those credits to get training on moving your business-critical apps from the server closet (it’s probably full of monsters after all) to Google Cloud. These labs will help you prepare for the move:

  • Deploy an app that says “hello world and happy Halloween!” from the cloud with the App Engine: Qwik Start lab.  This lab is part of the Baseline: Deploy & Develop quest. Enroll in the quest and get hands-on experience with the Google App Engine framework by launching Python, Ruby, and Java apps (just to name a few). 
  • Networking 101: Learn how GCP might differ from an on-premises setup. “Good explanation,” said one reviewer 2 days ago.
  • Already using containers on-prem? Learn how to do it on the cloud with Google Container Engine. This lab earned seven 5-star reviews in the last 24 hours. 
  • The phrase “data loss” is almost as scary as meeting a werewolf in a creepy forest when you’re holding a rare hamburger. Learn how to use the Data Loss Prevention API to inspect a string of data for sensitive information and redact any that you find. The Data Loss Prevention API provides programmatic access to a powerful detection engine for personally identifiable information and other privacy-sensitive data in unstructured data streams. Try it with a lab.
  • Uh-oh, your app has a bug in it. Learn how Stackdriver APM (Application Performance Management) can help you detect, track, and debug errors in your application with this lab. And mind the monster socks!

Happy Halloween!

Become a data scientist without a PhD: Part 2

Remember that $1.2 trillion business value of AI? Just released, a new set of data science labs zoom in on Google Cloud’s data science and ML tools.  Enroll in the Data Science on GCP: Machine Learning quest by Monday, November 15th and you’ll get 1 month pass to Qwiklabs (free of charge, no CC required). You’ll run machine learning jobs with state-of-the-art tools and real-world data sets.

There are over 8,500 Data Scientist jobs on LinkedIn. 68% of those jobs require machine learning expertise. As a data scientist, you will transform data to:

  • Improve revenue, business agility, customer experience
  • Reduce costs
  • Development of new products and or product features

Don’t have these skills, or want to improve? You don’t need a PhD. Learn how to do all of these things and more with a lab. Here are some of the labs:

  1. Machine Learning with Spark on Google Cloud Dataproc lab: Analyze data using Spark with the PySpark interactive shell on the master node of the Cloud Dataproc cluster running on Google Cloud Datalab:

Then create and train a Spark Dataframe by importing, developing, saving and restoring a logistic regression model. You will then build data visualizations with Jupyter notebooks. In your model, does the on-time arrival probability rise with overall flight distance? Share your results @Qwiklabs!

2. Processing Time Windowed Data with Apache Beam and Cloud Dataflow (Java): You’ll configure Maven Apache using the starter project archetype for Cloud Dataflow projects:

Patience! This will take a few minutes to compile… When the build is successful, you should see something like this:

Finally! You’re ready to deploy a Java application to Apache Beam to create training and test data files.

If you are successful, you should see these files. Did you get it? Share your results! @Qwiklabs.

3. Bayes Classification with Cloud Datalab, Spark and Pig on Google Cloud Dataproc: Have you ever performed quantization of a data set? Here’s your chance. Use Dataproc, Datalab and Spark to perform quantization of a dataset to improve the accuracy of a data model. Then visualize your data with Jupyter notebooks and Apache Pig:

And don’t forget about part 1, the Data Science on GCP quest. Both quests cover the hands-on exercises described in Data Science on Google Cloud Platform book by Valliappa Lakshmanan (Lak).

New Quest: G Suite Integrations

G Suite has over 4 million customers today, and growing.  Are you one of them? Get the most out of G Suite and Google Cloud’s powerful tools. Just released, the G Suite: Integrations quest features 8 new G Suite labs, each one designed to make you look smarter than the one before. Get G Suite training on advanced tools like integrating BigQuery and Google Slides for data visualization and building your own custom apps for Google Sheets.

Complete all 8 labs and add the new G Suite badge to your resume. And if you’re one of the first 100 people to enroll using this link, you will receive 50 Qwiklabs credits free of charge (enough to complete the quest). Enroll now.

Here’s some of what you’ll do:

  1. Learn how to write code that accesses Google developer technologies, in just 4 lines of JavaScript.
  2. Use the Apps Script CLI, or clasp, to create and publish web apps and add-ons for products like Sheets, Docs, Forms, and Slides from the command line. In this lab you will learn to create, edit, and deploy Apps Script projects locally.
  3. Build a chatbot for Hangouts Chat. This one is “Attendance Bot” – you will learn to integrate it with a user’s vacation responder and meetings in Calendar. What kind of chatbot would improve your daily routine (and maybe lunchbreak)?
  4. Got a presentation coming up? Use Google Slides API as a Custom Presentation Tool. Learn to build a presentation using the Google Slides API and BigQuery to present an analysis of the most common software licenses. Take what you learn in the lab to your next presentation and knock your stakeholders’ socks off.
  5. More Big Data and Slides – learn how to leverage two Google developer platforms, G Suite and Google Cloud Platform (GCP), to collect, analyze and present data.                                                                                          
  6. Good luck on your quest! And don’t forget to share your badge when you complete it – @Qwiklabs – after all, you earned it.

Become a data scientist without a PhD

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:

      1. 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.
      2. 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:

You’ll also:

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!

Wherefore art thou, Machine Learning training?

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.

BigQuery training

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.

Big Data and Google Slides analysis

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.
Dataflow Pipeline trainingTensorFlow 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?

Tensorflow training

New Quest: IoT in the Google Cloud

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?

Enroll now.

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!

Google Cloud IoT badge

How they use Machine Learning to train self-driving cars

Interested in self-driving cars? Learn the technology behind the magic – then sit back, relax, and let the car do it for you.

  1. 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. 
  2. 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.
  3. 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.
  4. 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!

Back to school: Cloud training for educators

Jobs in the tech industry (machine learning, AI, Cloud) will grow between 12%–37% through 2022. Your computer science curriculum can unlock possibilities for students’ career advancement. Take advantage of free Google Cloud Platform training resources to help your students grow computer science skills:

    • If you’re associated with a non-profit university, complete this form to request free training on Qwiklabs and Coursera.

Next, use your benefit to have your students enroll in a few machine learning Quests:

  • Baseline: Data, ML, AI Quest: Since machine learning is growing rapidly in the tech industry, help your students get started with data tools like Cloud SQL, BigQuery, APIs, Bigtable, Dataproc, Dataprep, and Cloud ML Engine. If your students are interactive learners, they can follow along Mark as he guides their path.
  • Machine Learning APIs Quest: Give your students the opportunity to work with a handful of machine learning APIs. For example, they’ll work with Translation API and Natural Language API to translate text into other languages. They’ll also work with Cloud Vision API to capture text from images and Google Cloud Dialogflow to build a responsive chat bot.
  • Data Science on GCP Quest. Challenge your students to use Tensorflow, Dataflow and Data Studio to practice all aspects of datasets, such as ingestion, exploration, visualization, etc.

Fun fact: This Quest is derived from the book, Data Science on Google Cloud Platform by Valliappa Lakshmanan. Lak is on a mission to democratize machine learning. If your students were to read the book, they will learn how to apply statistical and machine learning methods to real-world problems.

If your class is interested in learning about the fundamentals of Google Cloud in-person, register for a study jam. Your students will get free access to the GCP Essentials Quest during the session and you’ll get two days of free lesson plans. If they complete the Quest within 1 month of their session, they’ll get a 30-day pass to Qwiklabs (free of charge, no CC required). They can use the pass to tackle any of the machine learning Quests mentioned above.

Why wait? Take advantage of these programs and set your students up for success by helping them add these badges to their resumes:

        

Machine Learning for .NET developers

Democratizing machine learning continues, this time for .NET. Google Cloud is committed to supporting developers getting their .NET workloads up and running on the GCP. Enroll in the Developing Data and Machine Learning Apps with C# and you’ll get 35 Qwiklabs credits, good towards labs in the new Quest (free of charge, no CC required).

Each lab demonstrates how to hook up your data to Google’s ML tools with just a few simple commands. You even get app templates you can re-use when you work on your own projects.

  • Using BigQuery with C# (60 mins): To  or not to , that is the question. Use BigQuery to analyze Shakespeare, a GitHub dataset and data you upload yourself (could be anything).
  • Using the Natural Language API with C# (45 mins): Analyze how awesome Yukihiro Matsumoto is, with documentSentiment. What did you get? The overall sentiment analysis consists of two fields: sentiment and magnitude. Sentiment ranges between -1.0 (negative) and 1.0 (positive). Magnitude indicates the overall strength of emotion (both positive and negative) within the given text, between 0.0 and +inf. Pop quiz: who remembers how to diagram a sentence? Now you can #makegoogledoit, one more talent of the Natural Language API.
  • Using the Speech-to-Text API with C# (45 mins): How many languages do you speak? The Google Cloud Speech-to-Text API has 120 different languages and variants. Even French or a Brooklyn accent. For extra credit, see if the API can transcribe a clip of your speech when you take the lab. Check it out on TechCrunch (:
  • Using the Video Intelligence API with C# (45 mins): You’ll work with a shot-change detection example in this lab. What other types of changes would you want to identify? Maybe a model that detects activity in wildlife monitoring cameras or security footage…
  • Using the Vision API with C# (45 mins): What do otter crossing signs have in common with the Eiffel Tower? The Google Cloud Vision API can recognize them both. Learn how to protect wildlife and organize your vacation photos with a lab. Then apply the skills you learned next time you build a license plate recognition app, or rank the most popular landmarks #teampixel is sharing.

  • Using the Translation API with C# (45 mins): How do you say “hello world” in Turkish? I don’t know – but we can use the Translation API to do it for us. Text is translated using the Neural Machine Translation (NMT) model. If the NMT model is not supported for the requested language translation pair, then the Phrase-Based Machine Translation (PBMT) model is used. And “hello world” in Turkish? Selam Dünya!
  • Cloud Spanner: Create a Gaming Leaderboard with C# (60 mins): Ready player one – wait, who won the last round? Learn to create a leaderboard with C# – this one is the most advanced lab in the Quest so prepare to be challenged!

Hurry, click here to enroll by the weekend and get 35 credits to help you get started. Good luck!