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.