Course – Cloud Computing
Google Cloud Platform (GCP) Training
5 Days / 40 HrsAll LevelsClassroom / Live Virtual
Duration
5 Days / 40 hrs
Level
All Levels
Format
Classroom / Live Virtual
Domain
Cloud Infrastructure · Google Cloud
Training Methodology
Learning by Doing
Every module pairs a GCP concept with a hands-on console lab, ending in a full capstone cloud solution build.
01
Explore
Hands-on console labs from Day 1.
02
Experiment
Work across compute, storage, and networking.
03
Engage
Real deployment and CI/CD scenarios.
04
Apply
Capstone cloud solution build.
Who This Is For
What You’ll Be Able to Do
- Navigate and manage GCP resources across the global infrastructure and resource hierarchy
- Deploy and manage applications using Compute Engine, App Engine, and Cloud Functions
- Configure secure networking (VPC, firewall rules, load balancing) and Identity & Access Management
- Implement storage and database solutions across Cloud Storage, Cloud SQL, Firestore, and BigQuery
- Work with containers and Kubernetes (GKE), and build CI/CD pipelines with Cloud Build and Terraform
- Design cloud-native architectures with monitoring, security, and cost optimization built in
Prerequisites
- Basic understanding of networking and Linux/command-line fundamentals recommended
- No prior GCP experience required
Curriculum
Day 1
GCP Fundamentals & IAM
- Cloud computing concepts (IaaS/PaaS/SaaS), GCP global infrastructure, resource hierarchy
- IAM fundamentals — users, groups, service accounts, roles; least privilege
Labs: Create GCP free tier account, navigate Cloud Console, configure billing, explore Cloud Shell; create IAM users, assign roles.
Day 2
Compute & Storage Services
- Compute Engine VMs, App Engine, Cloud Functions, managed instance groups & autoscaling
- Cloud Storage classes, bucket management, lifecycle policies, storage security
Labs: Deploy VM, configure startup scripts, deploy sample application; create storage buckets, configure lifecycle rules.
Day 3
Networking & Database Services
- VPC architecture, subnets, firewall rules, load balancing, Cloud DNS/CDN/NAT, VPN & Interconnect
- Cloud SQL, Firestore, Bigtable, Memorystore
Labs: Create custom VPC, configure subnets, deploy load balancer; create Cloud SQL instance and connect an application.
Day 4
Containers & Kubernetes, Security & Monitoring
- Docker fundamentals, GKE (pods, deployments, services, ingress), Artifact Registry
- Cloud IAM, Security Command Center, Cloud Armor; Cloud Monitoring, Logging, Error Reporting
Labs: Build Docker image, push to Artifact Registry, deploy to GKE; configure alerts, monitor VM resources, create dashboards.
Day 5
Data Engineering, DevOps/CI-CD & Capstone Project
- BigQuery, Dataflow, Pub/Sub, Dataproc; Cloud Build, Cloud Deploy, Source Repositories, Terraform
- Capstone: build a complete cloud solution — web app, Cloud Storage, Cloud SQL, monitoring, security, load balancing
Labs: Load data into BigQuery and run analytical queries; build a CI/CD pipeline; capstone cloud solution build.
Delivery Details
- Delivered as classroom or live virtual instructor-led — scheduled around your team
- 30% Lecture / 70% Hands-On Labs against the GCP Console and Cloud Shell