Introduction to Google Cloud
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Here's an intro to the 30 Days of Google Cloud program to kickstart your career in the cloud as well as earn exciting prizes & digital badges. To start with, your facilitator, Mohini Gupta, will be taking you on board this journey, explaining you these : 1.) Introduction to the program 2.) About GCP Crash Course 3.) A Tour of Qwiklabs and the Google Cloud Platform Lab 4.) Hands-on lab experience
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Introduction to Google Cloud
- 1. 30 Days of Google Cloud
- 2. ABOUT ME Flutter Developer 30 Days of Google Cloud Campus Facilitator linkedin.com/in/mohini-gupta-0106 github.com/Mohinig @mohinigupta_01
- 3. Session Agenda 5 min1 What is Cloud?2 #30Days of Cloud track3 Demonstration of lab and hands on experience. 4 How to get help ?5 Introduction to 30 Days of Google Cloud program 5 min 10 min 30 min 5 min QnA6 5 min
- 4. NOTE: This program is only for students who have Developer Student Circle (DSC) on their campus.
- 5. Go Cloud!
- 7. What is Cloud? … as a service > > PlatformInfrastructure Software
- 8. No need to manage your own infrastructure. Use managed services instead. Cloud Storage Cloud Bigtable Cloud Datastore Cloud SQL Cloud Spanner CustId App Engine Container Engine User data management Payment etc. API gateways for other backend apps Application Data Object data like multimedia High-volume or semi-structured data like streaming or gaming data Relational data Application Logic Integration with other Google services Google Maps, YouTube, and more Name
- 9. Get Set!
- 10. Track 1: Cloud Engineering Track 2: Data Science & Machine Learning Here are the 2 tracks Now let’s go over the different tracks that we have in the program on which you will be trained first and then you have to train your peers. Contents of the program
- 11. Track 1: Cloud Engineering 1. Getting Started: Create and Manage Cloud Resources 2. Perform foundational infrastructure tasks in Google Cloud 3. Setup and Configure a Cloud Environment in Google Cloud 4. Deploy and Manage Cloud Environments with Google Cloud 5. Build and Secure Networks in Google Cloud 6. Deploy to Kubernetes in Google Cloud
- 12. Track 2: Data Science & Machine Learning 1. Getting Started: Create and Manage Cloud Resources 2. Perform Foundational Data, ML, and AI Tasks in Google Cloud 3. Insights from Data with BigQuery 4. Engineer Data in Google Cloud 5. Integrate with Machine Learning APIs 6. Explore Machine Learning Models with Explainable AI
- 13. Google Cloud Skill Badges What is a skill badge? An exclusive digital Google Cloud skill badge demonstrates your growing Google Cloud recognized skillset. How do I earn a skill badge? Show your cloud skills by completing a series of hands on labs, including a final assessment challenge lab, to test your skills and earn a Google Cloud skill badge to share with your network. Show us your skills by earning all of them!
- 14. Let’s get started! Open a new incognito window.
- 16. Getting Started: Create and Manage Cloud Resources
- 17. Enroll in the Getting Started: Create and Manage Cloud Resources Quest Click on the “Enroll in this Quest” button
- 18. The quest has 6 labs. We will go through 1 of them together as a group and you have to take the rest yourself. As said earlier, you need credits to take these labs. You can use your 600 credits to access these labs. Getting Started: Create and Manage Cloud Resources Introductory 6 Steps 5 hours 13 Credits In this introductory-level Quest, you will get hands-on practice with the Google Cloud’s fundamental tools and services. HANDS-ON LAB A Tour of Qwiklabs and the Google Cloud Platform HANDS-ON LAB Creating a Virtual Machine HANDS-ON LAB Getting Started with Cloud Shell & gcloud HANDS-ON LAB Kubernetes Engine: Qwik Start HANDS-ON LAB Set Up Network and HTTP Load Balancers HANDS-ON LAB Getting Started: Create and Manage Cloud Resources: Challenge Lab
- 19. A virtual machine is a software-based computer Physical Computer Virtual Machines in a Physical Computer
- 20. LAB WALKTHROUGH Lab : Creating a Virtual Machine (Getting Started: Create and Manage Cloud Resources) Objectives ● Create a virtual machine with the Google Cloud Platform Console. ● Create a virtual machine with gcloud command line. ● Deploy a web server and connect it to a virtual machine. Compute Engine
- 21. Data Science & Machine Learning Track
- 22. ● Gain insights from data using Google Cloud’s pre-trained machine learning models ● Leverage same technology as Google Photos and Google Assistant ● Require ZERO prior knowledge of ML Google Cloud Machine Learning APIs
- 23. Google Cloud Machine Learning APIs Vision Video Intelligence Speech To Text Natural Language Translation
- 24. Perform Foundational Data, ML, and AI Tasks in Google Cloud
- 25. Google Cloud Speech to Text API ● Google Cloud Speech-to-Text enables developers to convert audio to text by applying powerful neural network models in an easy-to-use API. ● The API recognizes 120 languages and variants to support your global user base. ● It can process real-time streaming or prerecorded audio, using Google’s machine learning technology.
- 26. LAB WALKTHROUGH Lab : Google Cloud Speech API: Qwik Start (Perform Foundational Data, ML, and AI Tasks in Google Cloud) Objectives ● Create an API Key ● Create your Speech API request ● Call the Speech API Google Cloud Speech API
- 27. Getting help
- 28. Need Help? 1. There is online chat support available 24/7 for Qwiklabs. Select the Department as “30 Days of Google Cloud” Look at the bottom right corner of your screen
- 29. Need Help? 2.You can fill the form bit.ly/dsciem2020 and join the discord channel #30DaysofCloud. I will be there to respond along with the DSC team.
- 30. Need Help? 3. Google it! Review support documentation at cloud.google.com/docs
- 31. Need Help? 4. If there any other problems, email dscsupport@qwiklabs.com The team there will respond quickly.
- 32. Complete remaining quests in Cloud Engineering track Getting Started: Create and Manage Cloud Resources What are skill badges? An exclusive digital Google Cloud skill badge that demonstrates your growing Google Cloud recognized skillset. Perform Foundational Infrastructure Tasks in Google Cloud Setup and Configure a Cloud Environment in Google Cloud Deploy and Manage Cloud Environments with Google Cloud Build and Secure Networks in Google Cloud Deploy to Kubernetes in Google Cloud Earn “Skill Badges” simultaneously!
- 33. Earn all these badges! Getting Started: Create and Manage Cloud Resources Perform Foundational Infrastructure Tasks in Google Cloud Deploy and Manage Cloud Environments with Google Cloud Build and Secure Networks in Google Cloud Deploy to Kubernetes in Google Cloud Setup and Configure a Cloud Environment in Google Cloud
- 34. Complete remaining quests in Data Science & Machine Learning track Getting Started: Create and Manage Cloud Resources What are skill badges? An exclusive digital Google Cloud skill badge that demonstrates your growing Google Cloud recognized skillset. Perform Foundational Data, ML, and AI Tasks in Google Cloud Insights from Data with BigQuery Engineer Data in Google Cloud Integrate with Machine Learning APIs Explore Machine Learning Models with Explainable AI Earn “Skill Badges” simultaneously!
- 35. Earn all these badges! Getting Started: Create and Manage Cloud Resources Perform Foundational Data, ML, and AI Tasks in Google Cloud Engineer Data in Google Cloud Integrate with Machine Learning APIs Explore Machine Learning Models with Explainable AI Insights from Data with BigQuery
- 36. Share your achievement Share your newly earned badge on social media using the tag #30DaysofGoogleCloud. This is a great achievement and we would love to celebrate this with you. Follow us @GoogleCloud_IN and @GoogleDevsIN @dsc_iem
Editor's Notes
- Now it’s time to introduce you to the 30 Days of Google Cloud program, but before that let’s dive into why should you consider building a career in cloud right now.
- [Read out the agenda on this slide.]
- The learning opportunities with Google Cloud are a great way to prepare for cloud careers. What’s possible with cloud? Let’s look at an example that we are all likely familiar with.
- There are three main types of cloud-based services: Infrastructure as a service Platform as a service Software as a service
- Consider the infrastructure needed for an online game. You can use Google Cloud services to store: Object data such as image and video files High-volume or semi-structured data such as streaming or game data Relational data such as user id, name and so on There are multiple options such as Kubernetes Engine for your application runtime environment. This is where your application code executes. You can also build apps which use other services like Google Maps and YouTube. With cloud-based services, you don’t have to set up and manage your own infrastructure. You can simply focus on developing your app and then use managed cloud services to make it available globally in just a few minutes!
- Now it’s time to introduce you to our hands on learning platform, Qwiklabs. We hope that by now you have created your Qwiklabs account and have also redeemed the 600 credits that you would need for the program. If you have still not done that, then please follow the steps that I am about to show in order to get them.
- [Read the content on the screen] Let’s go over each track one by one.
- First track that we have in the program is the “Cloud Engineering” track. By completing the quests under the Cloud Engineering track, you will learn to explore and deploy solution elements, including infrastructure components such as networks, systems, and applications services. We have a total of 6 quests under this track and you will be doing the first one today i.e. Getting Started: Create and Manage Cloud Resources. The rest of the quests you will have to complete on your own by the end of this week. Not to worry, we will provide you with enough support so that you can complete them.
- Next, we have the “Data Science & Machine Learning” track. By completing the quests in this track, you will learn and demonstrate proficiency in key topics related to big data and machine learning to prepare for roles such as data analyst, marketing analyst, business intelligence professional, and data engineer. This track also consists of 6 quests and we will be doing Perform Foundational Data, ML, and AI Tasks in Google Cloud quest today.
- After completing each quest from either of the tracks, you have a chance of earning Google Cloud Skill Badges. Skill badges are used to show that you have actually applied your new learned skills using a challenge lab at the end where you have to take your new learned skills for a test drive.
- Incognito window makes it easier for you to understand the whole process from scratch.
- You are all set to take part in the hands on lab experience now. As discussed previously, today we will be going through the Getting Started: Create and Manage Cloud Resources quest - one of the foundational quest on Qwiklabs that will help you get started with GCP.
- This is what you should see. Click on “Enrol in this Quest” button. Skip the video, if you saw a video after you enrolled and wait for the next steps.
- You should now see the 6 labs listed in the quest. We will go through the first lab in the quest together right now. The rest labs you will have to do on your own. We will give you a small intro for the rest labs as well so that you don’t face any difficulties.
- You’ve likely worked with a physical computer before. A physical computer has resources such as CPUs, memory, disk storage, network configuration, operating system, and other application software. A virtual machine is a software-based computer and like a physical computer it has resources like CPU, memory, operating system etc. A virtual machine uses the physical resources of the host that it is running on. Every virtual machine has virtual devices that provide the same functionality as physical hardware. They also have additional benefits related to portability, manageability, and security. For example, you can launch a virtual machine, run applications for some time, and then destroy the virtual machine when the resources are no longer needed. Images: https://pixabay.com/vectors/computer-case-desktop-network-156129/ https://pixabay.com/vectors/cloud-computing-host-server-2023902/
- Troubleshooting: For the first objective, make sure to use the exact configuration while creating the virtual machine i.e. same name, region/zone, machine-type etc. For the second objective in the lab make sure to use Cloud shell only.
- But Google does. And it has used this training data to train its models and exposed it as Machine Learning APIs. One great thing about these APIs is that they require ZERO prior knowledge of ML. Basically, Google Cloud handles the “training” aspect of machine learning - gathering data and building the predictive models - allowing you to jump straight to the “Predict” phase where you give the API data and get back information.
- Speaker Notes: Google Cloud provides several pre-trained machine learning models. You can build applications with ML, even if you are not an ML expert. Here are our five Google Cloud Machine Learning APIs - Vision, Video Intelligence, Speech, Natural Language, and Translate. Demo the Speech to Text API Links: cloud.google.com/vision - cloud.google.com/video-intelligence cloud.google.com/speech-to-text - maybe ask for a volunteer from the audience cloud.google.com/text-to-speech cloud.google.com/natural-language cloud.google.com/translate
- You are all set to take part in the hands on lab experience now. As discussed previously, today we will be going through the Perform Foundational Data, ML, and AI Tasks in Google Cloud quest.
- We’ve got a few ways to get help while you are completing the quest.
- We’ve got a few ways to get help while you are completing quests. [Give a small walkthrough by taking them to the Qwiklabs page]
- We’ve got a few ways to get help while you are completing quests.
- We’ve got a few ways to get help while you are completing quests.
- We’ve got a few ways to get help while you are completing quests.
- You need to complete the rest of the quests & skill badges remaining in the Cloud Engineering track! You would have already completed 2 labs in the Getting Started: Create and Manage Cloud Resources quest in this session - do remember to complete the remaining labs immediately after the session while the knowledge is still fresh. Also, remember we talked about skill badges earlier. It’s really easy to earn one when you have already completed a quest. All you have to do is complete one more challenge lab after completing the quest related to that skill badge. Let us explain how it works! [Give the students an example by taking them to first the “Google Cloud Essentials” quest and then the “Getting Started: Create and Manage Cloud Resources” skill badge]
- Once you complete all the quests & the skill badges from Cloud Engineering track, this is what your profile would look like. You would have earned all of these amazing badges issued by Google Cloud which you can share with your network and add to your resume and professional profiles and showcase that you have the necessary skills and hands on practice on Google Cloud.
- You need to complete the rest of the quests & skill badges remaining in the Data Science & Machine Learning track! You would have already completed one lab in the Perform Foundational Data, ML, and AI Tasks in Google Cloud quest in this session - do remember to complete the remaining labs immediately after the session while the knowledge is still fresh. Also, remember we talked about skill badges earlier. It’s really easy to earn one when you have already completed a quest. All you have to do is complete one more challenge lab after completing the quest related to that skill badge. Let us explain how it works! [Give the students an example by taking them to first the “Google Cloud Essentials” quest and then the “Getting Started: Create and Manage Cloud Resources” skill badge]
- Once you complete all the quests & the skill badges from Data Science & Machine Learning track, this is what your profile would look like. You would have earned all of these amazing badges issued by Google Cloud which you can share with your network and add to your resume and professional profiles and showcase that you have the necessary skills and hands on practice on Google Cloud.
- Share profile and pictures with your social/professional network. Use hashtag: #30DaysofGoogleCloud Do remember to follow us on Twitter to stay updated with all the latest information about Google Cloud.