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.
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!
Are you ready for Next week? Join Google Cloud for the event of the year. Grow your network, grow your skills, and learn about the growth of Google Cloud – what’s happening now, and what’s next. And even if you’re not in San Francisco, join a Next event near you. Find one here.
Get a head start today by familiarizing yourself with key cloud concepts. Cloud training is available online, on-demand and on the real cloud console (not a video, lecture, or slideshow). Check out these hands-on labs, and follow any of the links below in the next 24 hours and you’ll get 25 Qwiklabs credits free of charge to help you start your Google Cloud training journey:
- Kubernetes training – get an intro to GCP tools with the GCP Essentials Quest, then learn how to make container orchestration part of your own workflow with Kubernetes in the Google Cloud. Want a challenge? Deploy game servers on clusters and run the Cloud Vision API with the Kubernetes Solutions Quest.
- Data Engineer training – Did you know there are over 1,500 data engineering jobs on LinkedIn right now? Get your first experience with data tools like Cloud SQL, BigQuery, APIs, Bigtable, Dataproc, Dataprep, and Cloud ML Engine with the Baseline: Data Quest (Mark can help guide your path!). Then work with Dataproc, Tensorflow and more with the Data Engineering Certification Practice Quest. And if you’re looking for a real resume boost, consider getting certified.
- Machine Learning – Familiarize yourself with key concepts with the ML APIs Quest. And aspiring data scientists, there are labs for you too. The Data Science on the Google Cloud Platform Quest, just released, gives you hands-on experience with Tensorflow, Dataflow, and Data Studio.
Complete a Quest and you’ll earn a badge. A badge shows your “flight time” with Google Cloud, and differentiates you as someone with hands-on GCP experience. Click this link → log into Qwiklabs → you will get 25 Qwiklabs credits to help you tackle your next Quest. Hurry, link expires in 24 hours.
See you next week!
The U.S. will be celebrating its 242nd year of independence on July 4th. Set your own “independence” day – learn new skills and take your career where *you* want to go. Enroll in any of these Quests by Monday, July 8th and get a 30 day pass to earn these badges (free of charge, no credit card required). What skills can you add to your resume?
- Baseline: Infrastructure Quest: Learn to use Cloud Storage, deploy a containerized application with Google Kubernetes Engine, build a Docker image, create and deploy a Cloud Function, publish and consume messages, create a Cloud IoT Core device registry and use Cloud Spanner. Here’s the badge you’ll earn:
- GCP Essential Quest: This Quest has the best of both worlds! While it helps you get more comfortable with the Google Cloud, like spinning up a virtual machine, it also challenges you to configure key infrastructure tools through working with more advanced Stackdriver and Kubernetes concepts. Tackle the Quest to earn this badge:
- Application Development Quest: Think you’re a Java Jedi or a Python powerhouse? Well we’ve got challenging Quests for you! In these two Quests, you’ll either put your Java or Python skills to test by developing cloud-based applications using GCP services such as App Engine, Cloud Datastore and Cloud Spanner. Then integrate these services and deploy to an App Engine and a Kubernetes Engine. Are you excited to earn these badges?
4. Scaling Your Infrastructure Quest: Not for beginners! If you’re ready for an expert level Quest, this one’s for you. Learn how to: set up multiple NAT gateways, deploy an autoscaling Compute Engine, customize Stackdriver logging, set up Jenkins on Google Kubernetes Engine to help orchestrate your software delivery pipeline and use Spinnaker to continuously deploy the application when changes are made. You’ll earn this badge:
Celebrate your own independence day with us. Enroll by Monday, July 8th, get a 30 day pass (free of charge, no credit card required), and take charge of your career!
Fun fact: there are 1,829 open positions for machine learning engineers on LinkedIn. Do you want to become a machine learning engineer? It’s easier than you might think, and we can help with a Quest or two.
Tackle any of the Quests from the roadmap below and become a ML expert:
1. Enroll in Baseline: Data, ML & AI Quest – If you’re new to ML, it’s a perfect Quest! You’ll work with big data, machine learning and artificial intelligence services in Google Cloud, like Dataproc and Bigtable. Enroll now and get a free 30 day pass to earn this badge, plus as many others as you can (free of charge, no CC required). Hurry, link expires Thursday, June 21.
2. The Machine Learning APIs Quest: This is the next step in your ML journey. You’ll capture text strings from images, recognize characters translate text into other languages using Cloud Vision API, Natural Language API and Translation API. You’ll even build a responsive chat bot using Google Cloud Dialogflow and train & deploy a TensorFlow model to Cloud ML Engine for serving (prediction).
3. Enroll in Scientific Data Processing: Ready for a challenge? Tackle this Quest next. You’ll explore public domain scientific data sets, and learn to manipulate and transform data using the power of Google’s cloud infrastructure.
Can’t get enough of machine learning? Want to know what’s Next? Stay tuned for Part 2!