Google Cloud Training : Step By Step For Beginners to Advanced
Google Cloud Training Overview
Our Google Cloud Training provides hands-on experience in using Google Cloud Platform (GCP) services for computing, storage, networking, and machine learning. This course helps students, IT professionals, and developers gain practical skills in deploying, managing, and scaling applications on the cloud, preparing them for certification and industry projects.
Prerequisites
- Google Account
- Basic Knowledge of Cloud Computing
- Understanding of IT Infrastructure
- GCP Console Navigation
- IAM Configuration
- Programming Skills
- Billing Setup
Google Cloud Training Includes
- Compute Services
- Storage and Databases
- Networking
- Big Data and Machine Learning
- Developer Tools
- Management Tools
- Security
Key Highlights
- Scalability
- Global Infrastructure
- Enterprise-Grade Security
- Big Data and AI/ML Capabilities
- Open Source Friendly
- Developer-Friendly Tools
- Robust Cloud Ecosystem
Course Content
Learning Resources
- Google Cloud Training Platform(Google Cloud Skills Boost, Coursera)
- Official Documentation and Tutorials
- Practice and Hands-On Labs
Key Course Content of Google Cloud:
- Google Cloud Fundamentals:
- Introduction to Google Cloud
- Core GCP Services
- Networking and Security
- Data and Analytics
- Architecting with Google Cloud Platform:
- Design and Implement GCP Infrastructure
- Compute Services
- Storage and Databases
- Networking
- Security and Compliance
- Monitoring and Logging
- Data Engineering
- Data Engineering on Google Cloud
- Data Storage Solutions
- Machine Learning and AI
- Machine Learning with TensorFlow on Google Cloud
- Introduction to TensorFlow
- Google Cloud AI Services
- Advanced Machine Learning Techniques
Network Services:
- Google Virtual Private Cloud (VPC)
- Cloud Load Balancing
- Cloud CDN (Content Delivery Network)
- Cloud Interconnect
- Cloud VPN
- Cloud NAT (Network Address Translation)
- Traffic Director
- Network Service Tiers
- Cloud Armor
- Peering and VPN
Database Services:
- Cloud SQL
- Cloud Spanner
- BigQuery
- Firestore
- Cloud Bigtable
- Cloud Datastore
- Cloud Memorystore
- Cloud SQL for MySQL, PostgreSQL, and SQL Server
Road Map
- 1. Introduction to Cloud & GCP fundamentals
- 2. GCP Console walkthrough & billing setup
- 3. Identity & Access Management (IAM) basics
- 4. Compute: Compute Engine (VMs) — launch & manage
- 5. Compute: App Engine & Cloud Run (serverless)
- 6. Storage options: Cloud Storage, buckets & lifecycle
- 7. Databases: Cloud SQL (MySQL/Postgres) hands-on
- 8. Databases: Firestore & Cloud Bigtable overview
- 9. Networking: VPC, subnets, routes, and firewalls
- 10. Load Balancing, Cloud CDN and DNS
- 11. Monitoring & logging with Cloud Monitoring & Logging
- 12. IAM advanced: service accounts, roles & best practices
- 13. Security: Cloud Armor, KMS & data encryption
- 14. Compute autoscaling and instance groups
- 15. Containers: Docker basics & GKE introduction
- 16. Kubernetes on GCP: Deployments, Services & Scaling
- 17. CI/CD: Cloud Build, Cloud Source Repos & pipelines
- 18. Infrastructure as Code: Terraform on GCP
- 19. Serverless functions: Cloud Functions & event-driven apps
- 20. Messaging & streaming: Pub/Sub & Dataflow basics
- 21. BigQuery: data warehousing, SQL & performance best practices
- 22. Data ingestion & ETL: Dataflow & Cloud Storage pipelines
- 23. ML on GCP: AutoML & Vertex AI overview
- 24. Hands-on lab: Build & deploy a sample web app on GCP
- 25. Cost optimisation & resource tagging
- 26. Backup, snapshots & disaster recovery strategies
- 27. API management & Cloud Endpoints
- 28. Logging analytics & alerting playbooks
- 29. Real-world project #1: Scalable web application
- 30. Real-world project #2: Data pipeline & BigQuery analytics
- 31. Performance tuning & QPS testing
- 32. Identity federation & SSO integration
- 33. Compliance & governance on GCP
- 34. Advanced networking: VPC peering & Interconnect
- 35. Observability: tracing with Cloud Trace & Profiler
- 36. Migration strategies: lift-and-shift & refactor
- 37. Hybrid & multi-cloud patterns on GCP
- 38. Troubleshooting workshops & debug sessions
- 39. Preparation: sample exam questions & mock tests
- 40. Resume & interview coaching for cloud roles
- 41. CloudOps: automation with scripts and SDKs
- 42. GitHub/Gitlab workflows integrated with GCP
- 43. Logging & security audits (best practices)
- 44. Final capstone: design + deploy a production-ready solution
- 45. Project presentation & code review
- 46. Post-course support: doubt clearing sessions
- 47. Certification exam booking guidance
- 48. Placement assistance & employer introductions
- 49. Continuous learning resources & curated reading
- 50. Alumni community & project showcase
- 51. Optional advanced modules (AI/ML, DataOps)
- 52. Course wrap-up, certificate issuance & next steps
🎥 Free Google Cloud Training Videos
Watch our free Google Cloud (GCP) demo lectures and tutorials by expert trainers. Learn core concepts like Compute, Storage, Networking, and BigQuery directly from our classroom and online sessions.
Your Instructor
Learn from an industry expert with proven excellence in training, consulting, and mentoring.
Frequently Asked Questions — Google Cloud Training
This course is designed for IT students, developers, system administrators, DevOps engineers, data engineers and anyone wanting a practical path to Google Cloud Platform (GCP) skills and certifications.
Basic understanding of networking and OS concepts, familiarity with the command line, and a Google account. Programming knowledge (Python or similar) is recommended for data and ML modules.
The course covers material useful for Professional Cloud Architect, Cloud Engineer, Data Engineer and Associate Cloud Engineer certifications — with targeted modules and practice labs.
Duration varies by program: typical classroom or live-online batches run 8–12 weeks (part-time) or 4–6 weeks (fast-track). Modes: Live Online, Classroom Training and Recorded Video Lectures.
Yes — the training includes hands-on labs on GCP console, Compute Engine, Cloud Storage, BigQuery, Cloud Functions, IAM, networking, and at least two real-world projects.
Arth Training Institute provides resume guidance, mock interviews and placement support for eligible students. Contact us for current placement assistance details.
Fees depend on batch type (regular, weekend, fast-track) and group discounts. Please use the "Request for Free Demo Lecture" form or call +91 9374969705 for exact pricing and offers.
Yes — students receive a course completion certificate from Arth Training Institute. We also guide students for official Google Cloud certification exams (Google charges the certification exam fee separately).
Use the demo request form on this page or call/WhatsApp +91 9374969705 and email contact@arthtraininginstitute.com.
Career Opportunities After Google Cloud Training
After completing this Google Cloud Training at Arth Training Institute, you’ll be qualified for multiple cloud-based roles across IT, DevOps, and Data Engineering domains.
- ☁️ Google Cloud Engineer
- 🏗️ Google Cloud Architect
- 💻 Google Cloud Developer
- 📊 Google Cloud Data Engineer
- 🔒 Google Cloud Security Engineer
- ⚙️ Google Cloud DevOps Engineer
- 🤖 Google Cloud AI Engineer
- 🌐 Google Cloud Solutions Specialist
- 🎓 Google Cloud Certified Professional (after official exam)
- 🧩 Google Cloud Platform Consultant
Request for Free Demo Lecture
Fees Structure
Certification
