Dig deep into BigQuery Machine Learning with Google Cloud

You don’t need a B.S. in Computer Science to take advantage of powerful GCP data analysis tools. Google announced fully managed service at Next’18, BigQuery ML (BQML). BQML allows you to:

  • Create, train, evaluate, predict and deploy machine learning models with minimal coding
  • Use SQL directly in the database

Get started with BQML by taking the Predict Visitor Purchases with a Classification Model in BQML lab today and get a 30 day pass (free of charge, no CC required) to help you take advantage of this shiny new toy — I mean, seriously, an impactful data analysis tool!

Here’s some of what you’ll do in the lab:

  • Explore Ecommerce data & run the Query to find out what percentage made a purchase from website visitors:
  • Run the Query to find out your top 5 selling products: 
  • Preview the demo dataset to find useful features a machine learning model uses to understand if a first time visitor will return to make a purchase & dig deeper to know the risks of only using these fields for your classification model:
  • Evaluate classification model to maximize the True Positive Rate (predict that returning users will make a purchase) & visualize a ROC (Receiver Operating Characteristic) curve to maximize the area under the curve:Take the lab  and get your 30 day pass to be one step closer to earning the Data Engineering Quest badge.

The independence of upskilling

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? 

  1. 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:

  1. 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:

  1. 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!

Dig deep into Machine Learning with Google Cloud: Part 2

If you haven’t enrolled in the machine learning Quests mentioned in this blog, you’re missing out! One last chance for free labs, follow any of the Quest links in this post and get a 30 day pass to finish these Quests. Hurry, offer expires Thursday, June 28 (free of charge, no CC required).

Tackle any of the Quests from the roadmap below to become a ML master. If you’re a beginner… begin at the beginning 🙂

Earn a machine learning Quest badge or two, get practice with real-world scenarios, and make the most out of your time at Next ‘18 with some ML rockstars. Who might you meet at Next ’18?

Fei Fei Li is a Chief Scientist of Cloud AI and ML at Google Cloud. She works in the areas of computer vision and cognitive neuroscience. Her publications include Scaling Human-Object Interaction Recognition through Zero-Shot Learning  and Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks. Get hands-on practice with Cloud AI at scale with the Machine Learning APIs Quest.

Or you might run into Valliappa Lakshmanan. Lak is on a mission to democratize machine learning so anyone can do it using Google’s infrastructure. Check out his latest book, Data Science on the Google Cloud Platform, explaining how to apply statistical and machine learning methods to real-world problems. And try it for yourself with a lab from the Scientific Data Processing Quest!

Take some labs ahead of time, gain a little experience, and ask better questions at the ML sessions offered at the Next ’18! Check out these sessions:

Can’t get enough of machine learning? When you register for Next ‘18, you will have the option to add some of these ML boot camps:

    • End-to-End Machine Learning with TensorFlow on GCP: You’ll go through the process of building a complete machine learning pipeline, covering ingest, exploration, training, evaluation, deployment and prediction.
    • Building and updating a Machine Learning Model on Edge Network using Cloud ML: You’ll learn how to process and store IoT or other data using Cloud Pub/Sub, Cloud Dataflow, Cloud Storage, and Google BigQuery.
    • Building Chatbots with Machine Learning: You’ll use Dialogflow and Cloud Natural Language API to rapidly convert an HR manual document into a fully functional and conversational chatbot. You’ll also add text and voice interactions to the chatbot and secure and scale it for production.

If you can’t make it to Next in San Francisco, take classes worldwide. Find one here.

To make the most of your time at Next ’18, enroll in these ML Quests by Thursday, June 28 (free of charge, no CC required).

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!

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!