Join Google Cloud CEO Diane Greene and other experts for a free online conference on the future of artificial intelligence. The conference rolls through time zones too, so no matter where you are in the world, there’s a session for you.
Prepare yourself for deep-dives by taking cloud training ahead of time. Each of the following quests guides you through using GCP tools to answer an AI business question or solve a technical challenge. Use what you learn to ask the best questions and have the most meaningful conversations with your conference moderators. Use these links for a 1-month pass to Qwiklabs (free of charge, no CC required). Offer ends November 13th.
- Get your data insight-ready:
Enroll in the Baseline: Data, ML, AI quest to work with BigQuery, Cloud Speech API and Cloud ML Engine. Follow Mark as he guides your path in these 1-minute videos. You’re on your way to building a strong foundation in data management, cloud data warehouse and real-time analytics to implement AI.
2. Put AI to work, fast:
Enroll in the Data Science on GCP quests to practice data ingestion, preparation, exploration and visualization. Finish the first quest and move on to the next, which zooms in on running machine learning jobs with state-of-the-art tools and real-world data sets. The material for these quests comes from a book by Lak, who amongst others will elaborate on how data scientists, developers and others can incorporate AI into their products during the conference.
3. See AI in action:
Brush up on your ML skills with the Machine Learning APIs quest – some of my favorite labs guide you through use cases like image classification with Cloud Vision API and building an AI chatbot (: Then you’re well on your way to learn how businesses use AI to solve complex business problems like fighting fraud.
Think you can finish one of these quests in one month? Enroll now and be the stand-out participant at the conference!
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!
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:
- 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.
- 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)?
- 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.
- 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.
Good luck on your quest! And don’t forget to share your badge when you complete it – @Qwiklabs – after all, you earned it.
London lab-takers, you were awesome last week! Between admiring Lei-Mei’s socks, attending spotlight lab sessions, and binge-reading Data Science on the Google Cloud Platform, the big story was security. ‘Security built into every layer of the system’ stated Diane Greene, Google Cloud chief executive, emphasizing Google’s commitment to GCP’s reliability and integrity.
There’s lots of talk about Google Cloud’s security capabilities, but why not try it out for yourself? Get hands-on experience with GCP’s powerful security features with cloud security training labs. Complete all 8 labs and you will earn the Google Cloud Security & Identity badge to show your experience.
And today, help us test a new feature and get 45 free Qwiklabs credits for your time. Use this link to enroll in the quest and enter code 1423 into this field:
You should see 45 credits added to your account free of charge. If you do not see the credits right away, you may need to log out and log back in.
Here are some of the skills you will learn:
- Familiarize yourself with Cloud Security Scanner, a tool that identifies security vulnerabilities in your Google App Engine web applications.
- Learn how Key Management Service can help you secure access to your files in the cloud. Work with advanced features of Google Cloud Security and Privacy APIs, including setting up a secure Cloud Storage bucket, managing keys and encrypted data using Key Management Storage, and viewing Cloud Storage audit logs.
- In a private cluster, nodes do not have public IP addresses. This means your workloads run in an environment that is isolated from the Internet. Try it for yourself with the lab Setting up a Private Kubernetes Cluster.
Good luck! And remember, if it’s on the network, assume it’s a risk…but don’t worry, Google Cloud’s security tools can handle it.
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!
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:
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.