GCP Training

GCP Training

Google Cloud is the fastest-growing of the three major clouds — and GCP-certified engineers earn ₹10-25 LPA at mid-level. This two-month program covers the GCP services data + ML engineers use every day: Compute Engine, BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer (Airflow), Vertex AI, plus IAM and networking. Built around the Professional Data Engineer and Professional Cloud Architect certifications — pass either and you become significantly more hireable in 2026's GCP-growing market.

0 lessons

What you'll learn

  • Architect production data pipelines on GCP end-to-end
  • Run analytics at scale on BigQuery — handle petabyte queries efficiently
  • Build streaming pipelines with Dataflow + Pub/Sub
  • Train + deploy ML models on Vertex AI with full lifecycle support
  • Orchestrate workflows with Cloud Composer (managed Airflow)
  • Implement IAM + VPC + Cloud Load Balancing for production systems
  • Optimise GCP bills with the right service + tier choices
  • Pass GCP Professional Data Engineer OR Professional Cloud Architect
  • Land GCP Data Engineer / Cloud Engineer roles paying ₹10-25 LPA

Technologies Taught

GCP Compute — Compute Engine, Cloud Run, Cloud FunctionsBigQuery — partitioning, clustering, BI Engine, BigQuery MLDataflow — Apache Beam for batch + streaming pipelinesPub/Sub for event-driven architecturesDataproc — managed Spark/Hadoop on GCPCloud Composer — managed AirflowVertex AI — model training, AutoML, pipelines, endpointsCloud Storage classes + lifecycle policiesIAM + VPC + Cloud Load BalancingCloud SQL + Spanner + Firestore + Bigtable

Training Unique Features

  • Hands-on labs on real GCP accounts (free-tier compatible)
  • Cover data engineering + ML workloads in parallel
  • Build 4 production-grade GCP projects — pipelines + ML deployment
  • Daily 90-minute live class with live GCP console walkthroughs
  • Professional Data Engineer + Professional Cloud Architect prep included
  • Cost optimisation patterns — every GCP service has cost levers
  • Trained by GCP Professional-certified instructors with 10+ years experience
  • Mock interviews covering services + system design + cost analysis
  • Resume + LinkedIn polish for GCP roles
  • Direct intros to GCP-first companies actively hiring

You Can Work As

GCP Data EngineerGCP DeveloperGCP Cloud ArchitectBigQuery SpecialistGCP DevOps EngineerGCP ML EngineerCloud Data Engineer (GCP)

Upcoming In-Demand Jobs

GCP + AI EngineerVertex AI EngineerBigQuery Analytics EngineerGCP Platform Engineer

Training Curriculum

Why Cloud? And why GCP?

12 topics
  • •What is traditional IT environment and how it works
  • •Servers, storage, network in traditional IT
  • •What is cloud computing?
  • •Basic architecture of cloud computing
  • •Difference between traditional IT and Cloud computing
  • •Advantages of cloud computing
  • •Deployment Model and service model
  • •SAAS, PAAS and IAAS
  • •Private, Public and hybrid Cloud
  • •Why google cloud? And its exclusive benefits
  • •GCP locations
  • •Gartners Magic quadrant and market share

Cloud Computing and Basic Concepts

8 topics
  • •Overview of different cloud service providers
  • •Understanding regions and availability zones
  • •Exploring Google Cloud Platform (GCP) interfaces
  • •Introduction to Google Cloud Shell (Hands-on Lab)
  • •Step-by-step guide to creating a GCP account
  • •GCP Console walkthrough and navigation (Hands-on Lab)
  • •Managing organizations, folders, projects, and resources
  • •Configuring billing and setting up alerts (Hands-on Lab)

IAM (Identity and Access Management)

8 topics
  • •Fundamental concepts of Identity and Access Management (IAM)
  • •Overview of organizations, roles, members, service accounts, and policies
  • •Understanding Google Cloud's resource hierarchy
  • •Exploring different IAM roles and permissions
  • •Best practices for IAM implementation
  • •Assigning roles and conducting hands-on testing (Lab)
  • •Creating service accounts and assigning roles (Lab)
  • •Practice questions for review

Compute Engine

18 topics
  • •Introduction to Virtual Machines (VMs)
  • •Lifecycle of VM instances
  • •Various access options for VMs
  • •Creating Linux and Windows VM instances (Hands-on Lab)
  • •Different machine types and configurations
  • •Spot (Preemptible) instances and sole-tenant VMs
  • •Understanding VM images
  • •Overview of machine images
  • •Live migration and automatic restart of VMs
  • •Types of storage: Local SSD, persistent disk, and balanced persistent disk
  • •Deleting a VM and recreating it using a disk (Hands-on Lab)
  • •Understanding and managing snapshots
  • •Configuring firewall rules
  • •Pricing structure and available discounts
  • •Creating snapshots and setting up snapshot schedules (Hands-on Lab)
  • •Recovering VMs using snapshots (Hands-on Lab)
  • •Performing Compute Engine tasks in Cloud Shell (Hands-on Lab)
  • •Practice questions for review

Storage: Google Cloud Storage (GCS)

13 topics
  • •Introduction to Object Storage (Google Cloud Storage – GCS)
  • •Key features and use cases of GCS
  • •Understanding the structure of GCS
  • •Bucket naming conventions and best practices
  • •Creating a storage bucket and uploading objects (Hands-on Lab)
  • •Configuring IAM roles and ACL permissions for buckets (Hands-on Lab)
  • •Exploring different storage classes in GCS
  • •Implementing object versioning
  • •Managing lifecycle policies for storage optimization
  • •Understanding GCS pricing model
  • •Hands-on practice with versioning and lifecycle policies (Lab)
  • •Using GCS via gcloud commands (Hands-on Lab)
  • •Practice questions for review

Load Balancing and Autoscaling

9 topics
  • •Introduction to GCP Load Balancing and Its Features
  • •Various Types of Load Balancers in Google Cloud
  • •Differences Between Global and Regional Load Balancers
  • •Understanding Internal and External Load Balancers
  • •Overview of Internal and External HTTPS Load Balancing
  • •Key Components of a Load Balancer
  • •Auto Scaling: Concepts and Benefits
  • •Managed vs. Unmanaged Instance Groups
  • •Hands-on Lab: Setting Up an External HTTP Global Load Balancer with Auto Scaling

VPC (Virtual Private Cloud)

10 topics
  • •Introduction to Virtual Private Cloud (VPC) and Its Features
  • •Types of VPC: Default, Auto Mode, and Custom VPC
  • •Key Components of a VPC
  • •Understanding Internal and External IPs
  • •Routing in VPC: How Routes Work
  • •Firewall Rules and Their Configurations
  • •Overview of Shared VPC and Its Benefits
  • •VPC Peering: Concepts and Use Cases
  • •NAT Gateway: Functionality and Configuration
  • •VPC Pricing Structure and Cost Considerations

Project 1 – VPC and Compute Engine

8 topics
  • •Creating an Auto Mode VPC
  • •Setting Up a Custom VPC
  • •Configuring and Managing Subnets
  • •Deploying VM Instances Across Different Subnets
  • •Implementing Firewall Rules for Security
  • •Establishing VPC Peering for Network Connectivity
  • •Setting Up a NAT Gateway for Internet Access
  • •Practice Questions for Hands-on Learning

Cloud SQL

10 topics
  • •Introduction to Relational and Non-Relational Databases
  • •Types of Cloud SQL Databases
  • •Cloud MySQL: Features and Use Cases
  • •Cloud PostgreSQL: Overview and Benefits
  • •SQL Server in the Cloud
  • •High Availability (HA) in SQL Databases
  • •Creating a Cloud SQL Instance (Hands-on Lab)
  • •Setting Up a High-Availability (HA) SQL Instance (Hands-on Lab)
  • •Understanding Replication in Cloud SQL
  • •Backup Strategies and Best Practices

Cloud Spanner

6 topics
  • •Introduction to Cloud Spanner
  • •Comparison with Traditional Databases
  • •Key Features and Benefits
  • •Architecture: Regional vs. Global
  • •Understanding Replication in Cloud Spanner
  • •Backup and Restore Strategies

Big Data and Other Database / Storage Services

14 topics
  • •Understanding the Firestore Data Model
  • •Data Structure: Documents and Collections
  • •Overview and Key Features
  • •Use Cases and Benefits
  • •Notable Customers and Applications
  • •Challenges in Traditional Data Handling
  • •Overview and Features of Bigtable
  • •Use Cases and Real-World Applications
  • •Introduction to Data Warehousing
  • •Key Features and Benefits
  • •Pricing Considerations
  • •Introduction to Data Streaming
  • •Architecture and Working of Dataflow
  • •Key Features

Training Instructed By

MA
Mr. Aneesh KM---

16+ years of industry experience and 7+ years training experience in Google Cloud and Linux. Core Skills: Google Cloud, AWS, DevOps, Redhat Linux, Networking, Solaris, Storage/Datacenter. Approved trainer by Raj Cloud Technologies.

Approved trainer by Raj Cloud Technologies

Training content

ENDEDSun, 14 Jun, 03:40 am IST · 60 min

testing final

testing

Enrol to join
ENDEDSun, 14 Jun, 09:02 pm IST · 60 min

testing 2

testing

Enrol to join
ENDEDSun, 14 Jun, 10:34 pm IST · 60 min

testing

testing purpose

Enrol to join
ENDEDSun, 14 Jun, 11:45 pm IST · 60 min

testing 3'

qwert

Enrol to join
ENDEDMon, 15 Jun, 01:18 am IST · 60 min

123456

dfzgrdhtyjfkuil.khjg

Enrol to join

Lifetime access

Watch at your own pace

Certificate included

On 100% completion

Q&A community

Ask anything, get answers

₹21,999

One-time payment. Lifetime access.

Sign in to Enroll
Have questions?

Ask anything about this training

Curriculum, fees, schedule, EMI options — drop your question and our admissions team replies within one business day.

We reply within 1 business day · Your details are never shared

  • 0 on-demand lessons
  • Lifetime access
  • Certificate of completion