30 Days of Google Cloud
A complete package of knowledge, excitement, challenges and rewards
30 Days of Cloud, A complete package of knowledge, excitement, challenges and rewards. 30 days of cloud was facilitated at Maharaja Agrasen Institute of Technology, Delhi by Deepika Rana, DSC MAIT Lead for 2020–2021. The program kickstarted with an Introduction to the program, registration process and a discussion about the importance of cloud by the facilitator. The event was attended with 250+ Cloud enthusiasts and 90+ registrations for the program. 20+ students have already completed at least one tracks of the program with 50+ students currently working hard to earn the rewards, learn, and explore the cloud.
This program focused on two tracks targeting two major technical areas:
1. Cloud Engineering Track
2. Data Science and Machine Learning Track
All quests of Qwiklabs in both tracks followed either 6+1 or 7+1 labs approach with 6 training labs teaching the crux to nail the final challenge lab. The training labs were coupled with YouTube videos about the topic if you get stuck at any checkpoint of the lab. Checkpoints were like small tasks or the pathways you had to take to complete the goal. Each task of the lab was assigned a particular score which would lead the participant towards completion of the lab.
Cloud Engineering Track:
The cloud engineering track was broken into 6 skill badges representing the six infinity gems requires by a person to have the skills a cloud engineer would have.
The first quest dealt with creating and managing cloud resources, this was a common lab in both tracks and dealt in understanding the basics of cloud, like how to create a VM instance, understanding the cloud instances, Quick starting Kubernetes, Network and HTTP balancers and the final challenge lab was to test if the participant had enough knowledge to complete the assigned challenge and earn the first infinity stone.
The second quest aimed to give practical skills to the participant by making them understand about cloud bucket, cloud monitoring, cloud IAM, and some practical experience in the cloud terminal. The challenging task was to create a project to help a virtual team in storing pictures as memories, this used the concepts of creating a bucket, creating a cloud function, granting and revoking the access of a user.
The third quest was to Setup and Configure a Cloud Environment in Google Cloud. It was slightly advanced as dealt in managing SQL for BigQuery (the Query language in Google Cloud), Cloud SQL, monitoring cloud, managing VPC networks to test connectivity across various networks, full production deployment with google cloud, followed by managing deployment with Kubernetes. The challenge lab required the participant to set up a full deployment for a fictitious company Jooli Inc. thereby giving the participants work in a real-time challenge environment to create a cloud environment for a firm in an hour.
The fourth quest was to learn about Deploying and Managing a cloud environment on Google. The quest focused on Kubernetes, deployment manager, spinnaker and Kubernetes engine, managing multiple VPC networks and site reliability testing and troubleshooting. The challenge lab was associated with Jooli Inc. in which the participant was expected to use the skills acquired and deploy the created cloud environment and manage the deployed environment.
The fifth quest was focused on building and securing networks on google cloud, by developing the skills of User Identification using IAP (Identity Aware Proxy), Creating and Managing multiple VPC Networks, and Creating an Internal and HTTP Load balancer. The challenge lab expected the participants to help Jeff in deploying a very successful juice shop website to GCP.
The final quest of the cloud engineering track focused on deploying Kubernetes to the cloud. The participants were introduced to docker, working with Kubernetes managing deployment with Kubernetes and continuous delivery to the cloud with Jenkins. The challenge lab expected the participant to create a final deployment for Jooli Inc. by creating a Docker Image, testing it and pushing an image to create and expose deployment in Kubernetes and a pipeline in Jenkins to update the image whenever the source code changes.
The labs and challenges were challenging and they trained and tested the user to apply their skills in a real-life cloud challenge.
Data Science and Machine Learning Track:
The track was focused on preparing participants to work with Google Cloud Platform for data science and for building Machine Learning models by integrating the ML APIs available on Google Cloud Platform.
The First Quest of both tracks was similar and was focused to give an overview of the platform to the participant to make their learning smooth and heuristic. The track-focused on creating and managing cloud resources like VM instances, working with cloud terminal and cloud shell, setting up network and HTTP Load Balancers followed by working with Kubernetes engine.
The Second Quest was to perform fundamental AI and ML tasks in Google Cloud, this quest focused on Dataprep, a tool which reduces your data wrangling tasks significantly with a Google Sheet like interface and amazing way of handling the data, The quest also made the participant learn about DataFlow and DataProc to run Apache Spark and Hadoop clusters simply and efficiently. The quest also focused on cloud’s NLP, video intelligence and Speech API. The training lab was about implementing reinforcement learning in Google Cloud. The Challenge lab tested all the skills environment to check if the participant can complete the tasks in a time-bound environment.
The Third Quest focused on BigQuery a SQL like a query language interface in GCP it focused in the introduction to Big Query and SQL and converting the data insights to a presentation by integrating GCP and G Suite. The final lab was to create a report with Data Studio. The challenge lab focused on working with the COVID-19 data set and to perform Exploratory data analysis using BigQuery and to prepare a report to help the organization in planning and focusing healthcare efforts and awareness programs appropriately.
The Fourth Quest was focused in engineering data with the cloud, by creating a data transformation pipeline with Cloud Dataprep, building IoT Analytics pipeline in GCP, processing on the cloud using BigQuery, predicting prices using a classification in BQML and the final lab was to use Tensorflow and AI Platform to predict housing prices and copying BigQuery tables across various locations. The challenge lab was to predict the base fare when a taxi ride starts, this task was for a fictitious taxi company TaxiCab Inc.
The Fifth Quest was focused in integrating cloud with ML APIs the quest focused in heuristic development on ML skills of the participants by creating some mini projects like image captioning, face, landmark and label detection, Entity and Sentiment analysis and using the cloud vision API from the Kubernetes cluster. The challenge lab of this quest expected the user to perform a set of Machine Learning tasks for Jooli Inc. using the ML API available in GCP.
The Sixth Quest i.e. the final quest of this track focused on exploring machine learning models with explainable AI with main focus on the What-If tool for image recognition, fairness check, and to identify potential bias. The challenge lab of the quest expected the user to use the What-If tool, pull mortgage data, building an ML model and thereby predicting if an applicant would get the loan.
The completion of a particular track would impart knowledge about that particular domain in the participant and would make him/her eligible for a Google Cloud T-shirt and sticker pack. Whereas completion of both tracks will make the participant eligible for the T-shirts associated with each track and a Google cloud bag, along with stickers.
What participants have to say about 30 days of Google Cloud Program:
The 30 Days of Google Cloud was a great program as it helped me explore more advanced tools such as Dataprep, Dataflow, Dataproc etc. The 600 credits provided helped me attempt the expert level quests as well and being a facilitator for the program was a new experience altogether.
Deepika Rana, Lead DSC MAIT, Facilitator 30 Days of Cloud.
The labs were informative. I learnt a lot from them. The challenge labs were good in testing all concepts of previous labs.
The overall experience was excellent.
Sanyam Jain, MAIT
My experience was awesome, This course was very well managed, the labs were highly informative. The challenge labs were testing enough, I learnt new things as I’d have done face to face.
Mayank Gupta, MAIT
It was a great experience learning something new, especially which is going to help you in one way or the another. And know the various fields in which google cloud is efficient makes things more interesting. And when you have access to cloud implementation comes into play and makes things easy for you. So overall I would say it a very interactive course!
Sankar, MAIT
It was a great experience. I was already using Google cloud and learning from qwiklabs but I got lazy and left it. The 30 days of cloud gave me a boost of confidence and I did labs much faster. Because of this program, I have developed good skills in DevOps and I can use them to build awesome things.
- Naman Singhal
Thank you Qwiklabs for such an amazing platform and Thank You google for coming up with an engaging program.
See you in the cloud! ☁
