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This repository is mantained to track the progress of Hariket Sukesh Kumar Sheth, for the 30 Days of Google Cloud Program. All the labs and quests included under specific tracks of the Program are listed out. 12 quests alongwith Challenge Labs were supposed to be completed within 30 days of acceptance to the Program.

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#30DaysOfGoogleCloud

Follow the below steps for tracking Progress !!

๐Ÿ“ Step 1: Fork this repository. (You can see the fork option in the top-right corner.)

๐Ÿ“ Step 2: A separate copy of this repository would be opened in your own GitHub Account.

๐Ÿ“ Step 3: As soon as you complete any labs, you can track your progress here by editing the README.md file.

-> Change [ ] to [x] to check the checkboxes and track your progress throughout the program timeline.


* Track 1: Cloud Engineering Track

  • Getting Started: Create and Manage Cloud Resources: link
    • A Tour of Qwiklabs and Google Cloud
    • Creating a Virtual Machine
    • Getting Started with Cloud Shell and gcloud
    • Kubernetes Engine: Qwik Start
    • Set Up Network and HTTP Load Balancers
    • Create and Manage Cloud Resources: Challenge Lab
  • Perform Foundational Infrastructure Tasks in Google Cloud: link
    • Cloud Storage Qwik Start - Cloud Console
    • Cloud IAM: Qwik Start
    • Cloud Monitoring: Qwik Start
    • Cloud Functions: Qwik Start - Console
    • Google Cloud Pub/Sub: Qwik Start - Console
    • Perform Foundational Infrastructure Tasks in Google Cloud: Challenge Lab
  • Setup and Configure a cloud environment in Google Cloud: link
    • Cloud IAM: Qwik Start
    • Introduction to SQL for BigQuery and Cloud SQL
    • Multiple VPC Networks
    • Cloud Monitoring: Qwik Start
    • Managing Deployments Using Kubernetes Engine
    • Set Up and Configure a cloud environment in Google Cloud: Challenge Lab
  • Deploy and Manage Cloud environments with Google Cloud: link
    • Orchestrating the Cloud with Kubernetes
    • Continuous Delivery Pipelines with Spinnaker and Kubernetes Engine
    • Multiple VPC Networks
    • Troubleshooting Workloads on GKE for Site Reliability Engineers
    • Deploy and Manage Cloud Environments with Google Cloud: Challenge Lab
  • Build and Secure Networks in Google Cloud: link
    • User Authentication: Identity-Aware Proxy
    • Multiple VPC Networks
    • VPC Networks - Controlling Access
    • HTTP Load Balancer with Cloud Armor
    • Create an Internal Load Balancer
    • Build and Secure Networks in Google Cloud: Challenge Lab
  • Deploy to Kubernetes in Google Cloud: link
    • Introduction to Docker
    • Kubernetes Engine: Qwik Start
    • Orchestrating the Cloud with Kubernetes
    • Managing Deployments Using Kubernetes Engine
    • Continuous Delivery with Jenkins in Kubernetes Engine
    • Deploy to Kuberenetes in Google Cloud: Challenge Lab

* Track 2: Data Science and Machine Learning Track

  • Getting Started: Create and Manage Cloud Resources: link
    • A Tour of Qwiklabs and Google Cloud
    • Creating a Virtual Machine
    • Getting Started with Cloud Shell and gcloud
    • Kubernetes Engine: Qwik Start
    • Set Up Network and HTTP Load Balancers
    • Create and Manage Cloud Resources: Challenge Lab
  • Perform Foundational Data, ML and AI Tasks in Google Cloud: link
    • AI Platform: Qwik Start
    • Dataprep: Qwik Start
    • Dataflow: Qwik Start - Templates
    • Dataproc: Qwik Start - Console
    • Cloud Natural Language API: Qwik Start
    • Google Cloud Speech API: Qwik Start
    • Video Intelligence: Qwik Start
    • Perform Foundational Data, ML and AI Tasks in Google Cloud: Challenge Lab
  • Insights from Data with BigQuery: link
    • Introduction to SQL for BigQuery and Cloud SQL
    • BigQuery: Qwik Start - Console
    • Exploring Your Ecommerce Dataset with SQL in Google BigQuery
    • Troubleshooting Common SQL Errors with BigQuery
    • Explore and Create Reports with Data Studio
    • Insights from Data with BigQuery: Challenge Lab
  • Engineer data in Google Cloud: link
    • Creating a Data Transformation Pipeline with Cloud Dataprep
    • Building an IoT Analytics Pipeline on Google Cloud
    • ETL Processing on Google Cloud Using Dataflow and BigQuery
    • Predict Visitor Purchases with a Classification Model in BQML
    • Predict Housing Prices with Tensorflow and AI Platform
    • Cloud Composer: Copying BigQuery Tables Across Different Locations
    • Engineer Data in Google Cloud: Challenge Lab
  • Integrate with Machine Learning APIs: link
    • Introduction to APIs in Google
    • Extract, Analyze, and Translate Text from Images with the Cloud ML APIs
    • Classify Text into Categories with the Natural Language API
    • Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API
    • Entity and Sentiment Analysis with the Natural Language API
    • Awwvision: Cloud Vision API from a Kubernetes Cluster
    • Integrate with Machine Learning APIs: Challenge Lab
  • Explore Machine Learning Models with Explainable AI: link
    • What is the What-If Tool?
    • Getting Started with the What-If Tool
    • AI Platform: Qwik Start
    • Using the What-If Tool with Image Recognition Models
    • Using the What-if Tool Performance & Fairness Features
    • Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool
    • Compare Cloud AI Platform Models using the What-If Tool to Identify Potential Bias
    • Explore Machine Learning Models with Explainable AI: Challenge Lab

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This repository is mantained to track the progress of Hariket Sukesh Kumar Sheth, for the 30 Days of Google Cloud Program. All the labs and quests included under specific tracks of the Program are listed out. 12 quests alongwith Challenge Labs were supposed to be completed within 30 days of acceptance to the Program.

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