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
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.
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
10. Track 1: Cloud Engineering
Track 2: Data Science & Machine
Learning
Here are the 2 tracks
Now letโs 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!
17. Enroll in the Getting
Started: Create and
Manage Cloud
Resources
Quest
Click on the โEnroll in this
Questโ 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 Cloudโs 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
โ Create a virtual machine with
the Google Cloud Platform
Console.
โ Create a virtual machine with
gcloud command line.
โ Deploy a web server and
connect it to a virtual machine.
Compute Engine
22. โ Gain insights from data using
Google Cloudโs pre-trained machine
learning models
โ Leverage same technology as Google
Photos and Google Assistant
โ 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
25. Google Cloud Speech to Text API
โ Google Cloud Speech-to-Text enables developers to
convert audio to text by applying powerful neural
network models in an easy-to-use API.
โ The API recognizes 120 languages and variants to
support your global user base.
โ It can process real-time streaming or prerecorded
audio, using Googleโs machine learning technology.
26. LAB WALKTHROUGH
Lab : Google Cloud Speech API: Qwik Start
(Perform Foundational Data, ML, and AI Tasks in Google Cloud)
Objectives
โ Create an API Key
โ Create your Speech API
request
โ Call the Speech API
Google Cloud Speech API
28. Need Help?
1. There is online chat
support available 24/7
for Qwiklabs. Select
the Department as
โ30 Days of Google
Cloudโ
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.
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 โSkill Badgesโ 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 โSkill Badgesโ 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 itโs time to introduce you to the 30 Days of Google Cloud program, but before that letโs 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. Whatโs possible with cloud? Letโs 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 donโt 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 itโs 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]
Letโs go over each track one by one.
First track that we have in the program is the โCloud Engineeringโ 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 โData Science & Machine Learningโ 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 โEnrol in this Questโ 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 donโt face any difficulties.
Youโve 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 โtrainingโ aspect of machine learning - gathering data and building the predictive models - allowing you to jump straight to the โPredictโ 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.
Weโve got a few ways to get help while you are completing the quest.
Weโve got a few ways to get help while you are completing quests. [Give a small walkthrough by taking them to the Qwiklabs page]
Weโve got a few ways to get help while you are completing quests.
Weโve got a few ways to get help while you are completing quests.
Weโve 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. Itโs 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 โGoogle Cloud Essentialsโ quest and then the โGetting Started: Create and Manage Cloud Resourcesโ 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. Itโs 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 โGoogle Cloud Essentialsโ quest and then the โGetting Started: Create and Manage Cloud Resourcesโ 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.