This GCP MasterClass focuses on practical, real-world live projects that will help you learn Google Cloud services by doing—not just watching tutorials.
🎯 Why Learn GCP in 2025?
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In-demand skills: GCP skills are sought after in cloud engineering, data engineering, AI/ML, and DevOps roles.
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Global infrastructure: Google Cloud powers everything from YouTube to Gmail—reliable, scalable, fast.
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AI-native cloud: GCP is leading in AI/ML services and integration.
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Cost-effective for startups: GCP’s free tier and competitive pricing make it ideal for developers and small businesses.
🛠️ Prerequisites
Before diving into live projects, you should be familiar with:
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Basic Linux commands
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Cloud concepts (VMs, storage, networking)
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Scripting (Python or Bash preferred)
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Optional: Git, Docker, and Kubernetes basics
📦 Tools & Services You’ll Use in Projects
| Category | GCP Service |
|---|---|
| Compute | Compute Engine, Cloud Run |
| Containers | GKE (Google Kubernetes Engine) |
| Storage | Cloud Storage, Filestore |
| Databases | BigQuery, Cloud SQL, Firestore |
| AI/ML | Vertex AI, AutoML |
| Networking | VPC, Cloud Load Balancing |
| DevOps & CI/CD | Cloud Build, Cloud Source Repositories |
| Security & IAM | IAM, Cloud Identity |
| Monitoring | Cloud Monitoring, Logging |
🔥 GCP Live Projects (2025 Edition)
Project 1: Deploy a Scalable Web App on GCP
✅ Skills:
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Compute Engine
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Load Balancer
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Cloud Storage
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Cloud DNS
🧱 Description:
Build and deploy a basic Flask or Node.js web application on Compute Engine, use Cloud Storage for static content, and configure a global HTTP Load Balancer with autoscaling.
📈 Learning Outcome:
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Understand how to deploy web apps using virtual machines.
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Configure firewall rules and health checks.
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Set up a custom domain with SSL.
Project 2: Build a Serverless API with Cloud Functions
✅ Skills:
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Cloud Functions
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Cloud Pub/Sub
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Cloud Storage
🧱 Description:
Create a REST API using Cloud Functions that accepts image uploads. Upon upload, trigger a Cloud Pub/Sub message that processes the image and stores results in a bucket.
📈 Learning Outcome:
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Build event-driven architectures.
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Explore serverless development.
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Connect services using GCP triggers.
Project 3: Real-Time Data Pipeline with BigQuery and Dataflow
✅ Skills:
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BigQuery
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Dataflow (Apache Beam)
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Pub/Sub
🧱 Description:
Simulate streaming data (e.g., website events or IoT sensor data) into Pub/Sub, process it with Dataflow, and store analytics-ready data in BigQuery.
📈 Learning Outcome:
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Stream processing vs batch processing.
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BigQuery data modeling and SQL.
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Create visual dashboards with Data Studio (or Looker).
Project 4: Deploy a Machine Learning Model with Vertex AI
✅ Skills:
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Vertex AI
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AutoML
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Cloud Storage
🧱 Description:
Train and deploy a classification or regression model using AutoML or a custom model in Vertex AI. Integrate it with an API endpoint for predictions.
📈 Learning Outcome:
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Data preparation for ML
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Training and model deployment on GCP
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End-to-end ML lifecycle
Project 5: CI/CD Pipeline for a Microservices App on GKE
✅ Skills:
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GKE (Kubernetes)
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Cloud Build
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Artifact Registry
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Cloud Source Repositories
🧱 Description:
Create a microservices-based app (e.g., e-commerce) deployed on GKE with automated CI/CD pipeline using Cloud Build. Store container images in Artifact Registry.
📈 Learning Outcome:
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Kubernetes deployment on GCP
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Automate builds and rollouts
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GitOps-style deployment strategies
Project 6: Secure Multi-Tier Architecture with IAM and VPC
✅ Skills:
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VPC
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IAM
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Cloud SQL
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Compute Engine
🧱 Description:
Design a secure 3-tier architecture (web, app, DB layers), enforce IAM roles, and isolate network resources using VPC subnets, firewall rules, and service accounts.
📈 Learning Outcome:
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Secure cloud environments
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Role-based access control (RBAC)
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Network segmentation and best practices
📂 Project Hosting & Documentation
Document and share your GCP projects:
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Use GitHub for code and README documentation
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Take screenshots of GCP dashboard and architecture
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Record short demos or walkthroughs
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Publish case studies or blog posts on Medium or LinkedIn
🎓 GCP Certifications (Optional but Valuable)
If you’re aiming for a professional role, consider these certifications:
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Google Associate Cloud Engineer (Entry level)
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Professional Data Engineer (Data-focused roles)
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Professional Cloud Architect (For architects and consultants)
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Professional Machine Learning Engineer (ML model lifecycle)
Tip: Projects + Certification = Strong portfolio for job seekers.
✅ Final Tips to Master GCP with Projects
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Start small, but finish every project.
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Use the GCP Free Tier and $300 credit for practice.
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Follow best practices for security, IAM, and cost management.
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Join GCP communities, forums, and Google Cloud Discords.
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Keep experimenting—GCP evolves fast!
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