Dig deep into Machine Learning with Google Cloud

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!

This is the Quest you have been looking for…

You have been waiting patiently for a security training Quest…. today’s your lucky day! A new Quest from Qwiklabs, just released: Security & Identity Fundamentals. Dig deep into the building blocks of Google Cloud Platform Security by working with: Cloud Identity and Access Management (IAM), Network Security, setting up VPCs, VPNs and a private Kubernetes Cluster.

Are you ready to earn your Google Cloud Security and Identity badge? Click here to accept the challenge! (And use this link for 10 credits free of charge to help you along… click now, offer expires Friday.)

Here’s some of what you’ll do in this Quest:

Cloud IAM Custom Roles: Work with the right tools to manage resource permissions. Instead of directly granting users permissions, you grant them roles, which bundles permissions to map job functions within your company to groups and roles. Permissions management at scale? Yup.

Cloud Key Management Storage (KMS): Practice with advanced features of Google Cloud Security and Privacy APIs, set up a secure Cloud Storage bucket and manage keys and encrypted data using KMS. You’ll even use the Enron Corpus!

Virtual Private Cloud (VPC) Network Peering: Work with private connectivity across two VPC networks even if they don’t belong to same project or same organization. Plus, learn to save money with lower GCP egress bandwidth costs.

Cloud Security Scanner: Learn how to identify security vulnerabilities in your Google App Engine web applications. You will scan a sample app – can you find the vulnerabilities?

Data Loss Prevention: Practice with an intelligent data service, Google Cloud Dataprep, to visually explore, clean and prepare data for analysis. This one’s in beta so you’ll be one of the first to use it!

Private Kubernetes Cluster: Learn how to create a private cluster in the cloud environment. Since nodes in the private cluster do not have public IP addresses, your workload runs in an isolated environment from the Internet. This one’s a two-fer, which means if you complete this one lab, you’re making progress on both your Security & Identity Quest, and your Kubernetes in the Google Cloud Quest.

Ready to tackle this challenge? Enroll by Friday, June 22 and get 10 Qwiklabs credits free of charge (no credit card required).

 

 

Next ’18: Got your ticket?

Are you ready for the Next ‘18 conference? You’ll get access to Google keynotes, working sessions, exclusive certification opportunities, expert Q&A, opportunities to participate in bootcamps, and more. And if you can’t make it to San Francisco, check out these Next Extended events around the world. 

Next ’18 is the perfect opportunity to take a certification exam. Not sure where to begin, or how to prepare? Start your certification journey with hands-on labs. You can even take labs before the event so you get the most out of your experience at the conference.

Enroll in any of the following Quests, and get 30 credits free of charge (no credit card required). 

 1. The GCP Essential Quest is the most popular Quest of all time. Practice with GCP basics like starting a Virtual Machine and working with key infrastructure tools like Stackdriver and Kubernetes. Complete the Quest and you’ll earn this badge:

2. Need more specialized practice with the Google Cloud? Tackle the Baseline: Infrastructure Quest and you will 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:

3. Hoping to become a certified Google Cloud Architect? Next attendees who get certified will have exclusive access to the certification lounge (and snacks!). Complete the Cloud Architecture Quest to help you practice exam topics. Get in-depth experience with Identity and Access Management (IAM), infrastructure scenarios, Cloud Security and Privacy APIs, breaking an application into microservices, debugging, API call tracing and using Deployment Manager to establish alerts to trigger incident response. You’ll earn another badge, too!

4. Google’s Data Engineering certification is unique. Set yourself apart by earning this certification. Practice key exam concepts with the Data Engineering Quest (designed by Google’s training team). You’ll get experience with TensorFlow, an IoT pipeline, BigQuery and Datalab, and even learn how to correspond to your sales data with the weather! Here’s the badge you’ll earn:

See you at Next ’18!

 

 

TensorFlow with Machine Learning Engine and Datalab: There’s a lab for that

A Machine Learning algorithm walks into a bar. The bartender asks, “What will you have?”

The ML algorithm: “What’s everyone else having?”

If you laughed, you’re probably into machine learning. And because you laughed at our terrible joke, have one lab on us. Follow this link to take the lab “Using Distributed TensorFlow with Cloud ML Engine and Cloud Datalab” free of charge.

Here are the steps you’ll take to do the lab and be one step closer to earning your Google Cloud Solutions ll badge!

  1. Sign into Google Cloud Platform using the lab credentials:

You might have noticed – the lab instructions tell you to go to “Products and Services” but the menu in the console has changed. The cloud is always changing! When you see things like this, let us know (just click the yellow button  at the bottom-right of the screen) so we can improve the lab. Thanks!

2. Train the model on Cloud Machine Learning Engine

3. Visualizing the training process with TensorBoard

4. Draw a number with your cursor – can you think of anything else to sketch?

Did you see that red error message I got at first? Can you spot what happened?

Still can’t get enough of Machine Learning? Well, watch a short Machine Learning demo with Josh & Heather, practice with the Cloud ML Engine lab they demo (click the link in the YouTube description), then get more practice with the Using Distributed TensorFlow with Cloud ML Engine and Cloud Datalab.

Don’t forget to follow this link to get 25 Qwiklabs credits to take the lab and other Data and Machine Learning labs in the Google Cloud Solutions II Quest free of charge. Hurry, the link expires Friday, June 8th.

Your path to Google Cloud Architect Certification: Start with these Quests

Your company’s architecture:

If you want to keep data in sync across Region 1 and Region 2, do you know which product will enable you to do so?

 1. Google Cloud SQL

2. Google Cloud Bigtable 

3. Google Cloud Storage

4. Google Cloud Datastore

Did you know, or did you Google it? Over 70% of IT decision makers believe their organizations have lost revenue due to a lack of cloud expertise, about $258,188,279 per organization, according to this report. Companies are looking to hire people who can help. Cloud Systems Architects can make anywhere from $136k – $170k per year. Being a Certified Google Cloud Architect makes it easy to identify you as a person who can help with $258 million in lost revenue. Google can help you be the person with all the answers, starting with hands-on labs:

1. If you’re new to Google Cloud start with the Baseline: Infrastructure Quest to perform basic tasks in 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 perform basic operations in Cloud Spanner.

2. Thinking about getting certified? Tackle the Cloud Architecture Quest to help you prepare. Use this link to enroll in the Quest by Friday, May 25 and get 30 credits free of charge, to start your journey towards your next Google Cloud credential. Get in-depth experience with: Identity and Access Management (IAM), infrastructure scenarios, Cloud Security and Privacy APIs, breaking an application into microservices, debugging, API call tracing and using Deployment Manager to establish alerts to trigger incident response.

3. Then try the practice exam to assess your readiness. How did it go? Try to stay away from Google for this one…

4. Extra credit: Want to push your skills to the next level? Challenge yourself with the Scaling Your Infrastructure Quest, developed by Google experts. 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.

Since certification proves your ability to design, develop and manage dynamic solutions that are robust, scalable and highly available, it is a smart way to fast-track your cloud career in an accelerating industry with Google. And don’t forget, enroll in the Cloud Architecture Quest by Friday, May 25 and get 30 credits free of charge, to start your journey towards your next Google Cloud credential.

Are you going to Next ‘18? Get certified while you’re there and grow your network (pass the exam and you’ll get exclusive access to the certification lounge, too!).

 

Your next 3 labs should be…

If you feel excited about going to work, that’s great. However, if you go to work just to pay bills, then it might not be the career you’re looking for… Did you know that only 29% of professionals are engaged at work?

Disengaged employees cost the U.S. $450 billion to $550 billion per year. Think there’s a dream job waiting for you like these Kubernetes roles or these data roles, but afraid you lack the skills? Qwiklabs can help! Get the raise you’ve always wanted by making your mistakes and gaining valuable experience in a safe lab environment. These labs can help you ramp-up your skills (and if you follow the provided links, you can take a lab or two on us, free of charge):

  1. Don’t be intimidated by Machine Learning. This Cloud ML Engine Qwik Start Lab is perfect for newcomers to the field. It walks you through the basics of using machine learning on Google Cloud Platform. Start small, and before you know it, you’ll be able to analyze massive sets of your organization’s data to identify and resolve issues faster.

Check out how in this example you can experiment with TensorBoad graphs which show you your training model’s behavior:

  1. Don’t lose out on what your data can tell you. A NewVoiceMedia report reveals that U.S. companies are losing $62 billion to their competitors every year due to poor customer service. Want to ensure that your organization does not lose to its competitors? #MakeGoogleDoIt – more specifically, learn how Google can help you listen better to your customers with the Google Cloud Natural Language Qwik Start Lab. The Google Cloud Natural Language reveals the structure and meaning of text by offering powerful machine learning models in an easy to use REST API. Analyze interactions with your customers to understand their sentiment, and identify where you might be able to improve.

Here’s an example of how you’ll practice with the API entity analysis in the Google Cloud Natural Language Qwik Start Lab:

You can apply similar analysis to understand your customers, their pain points, and how your organization can help them reach their goals.

  1. Don’t be overwhelmed by Big data. Since big genomic data is here today, why not use it to ask bigger questions efficiently? Such as how can scientists develop treatments by combining drug and gene therapy? Get hands-on experience with enormous public datasets with the Google Genomics Qwik Start Lab. You’ll use Google’s implementation of the htsget protocol and SAM Tools to create a project that uses complex datasets. Practice with this lab and apply what you learn to securely store, explore, process and share your organization’s large and complex datasets.

Here’s an example of how in this lab you’ll practice running the query to view statistics about a small range on chromosome 11 on a public genome:

Don’t forget to follow this link and get 5 Qwiklabs credits to take these labs free of charge. And be sure to click by May 17, when the link expires!

5 steps to data mastery with Google Cloud

Have you seen the Make Google do it commercials? Learn how to make Google tackle the tough questions you want to answer for your job or business with 15+ Machine Learning and Big Data labs that can help you answer questions like:

How do self-driving cars know the speed limit? What SKUs will see the most traffic on my retail website when it’s raining? How can I analyze sentiment of my customers’ conversations with my team? And how can I prepare for Google’s Professional Data Engineer certification exam?

  1. Start with the Baseline: Big Data, ML, AI Quest if you’re new to Google Cloud. Get a basic understanding of GCP tools like Cloud SQL, BigQuery, APIs, Bigtable, Dataproc, Dataprep, and Cloud ML Engine, and explore public datasets like worldwide genomic data. With about five hours of lab work, you can earn your badge!
  2. Next, tackle more advanced concepts with the Machine Learning APIs Quest. This is where you’ll learn how to teach a self-driving car to recognize speed limit signs,   analyze blocks of text for customer satisfaction, and five more use cases. More fun with APIs, plus experience with Awwvision and Dialogflow.
  3. You’re ready for the next step, the Data Engineering exam practice Quest. These nine labs, designed by Google’s training team, help you practice critical job skills for the role of a Data Engineer. You’ll practice use cases with TensorFlow, an IoT pipeline, BigQuery and Datalab together, and you’ll learn how to correspond your sales data with the weather!
  4. Thinking about the Data Engineer certification? Try the practice exam to assess your readiness, and don’t “make Google do it” this time (: Set a timer and see how far you can get. How did it go?
  5. Extra credit: Challenge yourself with some of the most advanced labs on Qwiklabs today. The Google Cloud Solutions II Quest works through complex scenarios to knit multiple services together to solve a problem. The labs in this Quest come directly from engineers who developed these solutions in real-time. Not for the faint of heart! Dig deep into TensorFlow use cases, use BigQuery to explore NCAA data and build custom interactive dashboards with Boke, and more.

Why not try for a ML or Big Data Quest badge? A badge shows your “flight time” with Google Cloud, and differentiates you as someone with hands-on GCP experience. Would one (or more) of these badges look good on your resume?

 

Big Data & Machine Learning Challenge: May the fourth be with you

If you’re happy with your current job, that’s great! However, if you’re looking for a change, higher salary or maybe even a move within your current company, check out these data engineering opportunities. Qwiklabs can help you skill-up with relevant technologies.

Principal Engineer: A multinational technology corporation  is looking for Principal Engineers (AI, Deep Learning, Neural Machine Translation) in Dublin, IR, €101k – €141k (Glassdoor estimate)

Artificial Intelligence and Machine Learning Engineer: Canada’s leading communications company is looking for an Artificial Intelligence and Machine Learning Engineer in Toronto, CA,  $216k – $252k (Glassdoor estimate)

Machine Learning Engineer: A company focused on empowering their customers by their finances is looking for a Machine Learning Engineer in San Francisco, CA, $121k – $168k (Glassdoor estimate)

All of these job postings have one thing in common: data engineering. And if you’re looking for a qwik and effective way to get the training (plus a credential for your resume), Qwiklabs can help!

Start building your big data skills with the Baseline: Data, ML, AI quest. And since it’s May 4, here’s a Jedi mind trick – follow this link and you’ll get 3 Qwiklabs credits to take the first lab in the Quest free of charge. Then… complete the lab and earn an additional 10 Qwiklabs credits. Use that to complete the Quest. Hurry, the link expires at the end of the day, May 10!

This 10-lab quest gives you hands-on experience with core data engineering concepts. Complete the Quest and earn the Baseline badge, a Google Cloud Platform credential that you can add to your resume.

One of my favorite labs in this Quest is the BigQuery Qwik Start lab. Because BigQuery is serverless, there’s no infrastructure to manage. So as an engineer, you can focus your energy on finding meaningful insights from the data. Since BigQuery has a powerful foundation for real-time analytics, backed by Google’s accelerating infrastructure and compute power, you’ll be able to focus on analyzing what’s happening.

In the lab you’ll practice running this query which shows you how many times the substring ‘raisin’ appears in Shakespeare’s work:

You can apply similar analysis to your business data, for example, counting  words that convey certain sentiment like words such as “thank you”, “immediately” or “fix” appear in your customer communications, or how often specific words related to your product occur in customer searches on your site.

Another lab that you’ll take as a part of this Quest is the  Google Cloud Datalab. Google Cloud Datalab is an interactive data analysis and machine learning environment designed for Google Cloud Platform (GCP). You can use it to analyze and visualize your data interactively and to build machine learning models from your data. The screenshot below shows example labs, samples and other resources that you can explore in the Google Cloud Datalab.

By earning the Baseline: Big Data, ML, AI Quest badge, you will get valuable experience with different tools and methods for finding meaningful insights in your own data. If you earn a badge, it will help you prove your skills, when you’re submitting your resume for your next career move!

Don’t forget to follow this link to get 3 Qwiklabs credits to take the first lab in the Quest free of charge. Then… complete the lab and earn an additional 10 Qwiklabs credits. Use that to complete the Quest. Hurry, the link expires at the end of the day!

Your path to Google Cloud Certification: Start with a lab

Try answering this question:

Your company’s architecture is shown in the diagram. You want to keep data in sync across Region 1 and Region 2. Which product will enable you to do so?

  1. Google Cloud SQL

  2. Google Cloud Bigtable

  3. Google Cloud Storage

  4. Google Cloud Datastore

Google Cloud Certification practice exam

Do you know the answer?

That’s one of the questions on the Professional Cloud Architect certification practice exam. “Lack of cloud expertise is one of the top challenges enterprise companies face” according to this late 2017 report on moving to the public cloud. “Nearly three quarters of IT decision makers (71%) believe their organizations have lost revenue due to a lack of cloud expertise. On average, this accounts for 5% of total global revenue, or $258,188,279 per organization.”

Enterprise companies are looking for cloud experts. And being a Google Cloud Certified Professional Cloud Architect makes it easy to identify you as a person who can help with $258 million in lost revenue. But when it comes to earning a Google Cloud certification, where should you start?

The certification exam is designed to test your ability to build solutions with the Google Cloud Platform. The best way to prepare for a Google Cloud certification exam is experience. While there is no replacement for real world experience, hands-on labs can help you practice solving problem scenarios and learning to use GCP tools.

Enroll in the Cloud Architecture Certification Practice Quest and get 10 hands-on labs aligned with topics you’ll find in the certification exam outline. Use this link to enroll by April 9 EOD and get 5 credits free of charge to help you get started!

This Quest is designed to help you practice with tools and scenarios that will help you practice topics covered in the certification exam. Complete the labs and you’ll earn this Cloud Architecture badge, a cloud credential you can add to your CV.

Google Cloud badge

Here’s some of what you will do:

It’s a great day to take the next step in your career by adding a Google Cloud badge to your resume, and start your journey to certification!

Get started with Google BigQuery: Your first lab is on us

You want to get the most out of your data. But when you hear words like “public datasets”, “training data models”, and “correlation percentage”, your eyes glaze over. So how do you start taking advantage of Google Cloud’s data tools?

Here are some easy ways to get started.

  1. Watch and learn. Join Priyanka and Heather to learn how to get meaningful insights with Google BigQuery (4:39).

  2. Then, get hands-on practice with a hands-on lab for yourself. Just click the link below the YouTube video and follow instructions. Did you get your free Qwiklabs credits, to take your first BigQuery lab on us? Just be sure to click before April 2. And if you want to double-check your work, go back to the video and follow along with the demo, starting at 3:45.

  3. Ready for a little more of a challenge? Try the Weather Data and BigQuery lab, and practice correlating diverse data sets. And today only, this lab is featured for #1creditwednesday, which means this lab is available for 1 credit (normally priced at 5 credits).

In this lab, you will take a look at analyzing public data with BigQuery – starting with weather data from NOAA and citizen complaints data from New York City. 

Using public datasets, you will find what types of municipal complaints are correlated with weather. For example, you will find (not surprisingly) that complaints about residential furnaces are most common when it is cold outside:

Weather Data in BigQuery

What types of big data do you think you might correlate?

  • Weather and traffic volume on your retail website

  • Daily temperature in your town and foot traffic on your business’s street

  • NCAA winning percentages and uniform colors (there’s a lab for that!)

You can find the Weather Data and BigQuery lab here. Special today, the lab is available for 1 credit only (usually priced at 5 credits), so now’s the perfect time to check it out. Click the green button to start the lab. You’ll see a lower price than the screenshot below, today only.

Start the lab

See how the left panel changes? Those are your credentials to log into the Google console. Use these credentials (not your personal credentials) so Qwiklabs covers the cost of all your lab activities.

Sign into the Google Cloud Console

Next, you’ll need to accept the terms of service for the student account. Don’t worry about account recovery or emails – you won’t ever need to use this account again.

Agreements

Then you’re off on your lab! Follow the lab manual and at the end of the lab, you will have correlated two massive public datasets using BigQuery. What will you correlate next? We’d love to hear how you applied what you learned in the lab to your real-world data questions, let us know @Qwiklabs!