#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.

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* 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