The Google Cloud Platform (GCP) Data Engineering course provides hands-on training in designing, building, and managing data processing systems on Google Cloud. It covers topics such as data storage, data pipelines, data analysis, and machine learning on GCP, with a focus on practical application using tools like BigQuery, Dataflow, and Dataproc.
Demo: Internal and external IP
Lab: VPC Networking
Lab: Implement Private Google Access and Cloud NAT
Virtual Machines
Demo: Create a VM
Lab Intro: Creating Virtual Machines
Lab: Working with Virtual Machines
Demo: Custom roles
Lab: Exploring IAM
Storage and Database Services
Lab: Cloud Storage
Lab: Cloud SQL
Resource Management
Demo: Billing Administration
Lab: Examining Billing Data with BigQuery
Resource Monitoring
Lab: Resource Monitoring
Interconnecting Networks
Lab: Configuring Google Cloud HA VPN
Load Balancing and Autoscaling
Example: HTTP load balancer
Lab: Configuring an HTTP Load Balancer with Autoscaling
Lab: Configuring an Internal Load Balancer
Infrastructure Automation
Lab Intro: Automating the Infrastructure of Networks Using Terraform
Lab: Launch Infrastructure Solutions on Google Cloud Marketplace
Cloud Dataflow
Lab: A Simple Dataflow Pipeline (Python)
Lab: MapReduce in Dataflow (Python)
Dataproc
Lab: Running Apache Spark jobs on Cloud Dataproc.
Bigquery
Demo: Federated Queries with BigQuery.
Lab: Analyzing Data with BigQuery.