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#30DaysOfGoogleCloud

Follow the below steps for tracking Progress !!

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

📍 Step 2: A separate copy of this repository would be opened in your own GitHub Account.

📍 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