Google Cloud Platform (GCP) Training

Module 1: Introduction to Google Cloud

• Cloud computing fundamentals
• Google Cloud Platform overview
• Google Cloud architecture
• Regions and zones
• Google Cloud resource hierarchy
• Organizations, folders, and projects
• Google Cloud Console
• Cloud Shell
• Google Cloud CLI
• APIs and services
• Billing and cost management

Module 2: Google Cloud Compute Services

• Compute Engine
• Virtual machine instances
• Machine types
• VM images and disks
• Instance templates
• Managed Instance Groups
• Autoscaling
• Load balancing
• App Engine
• Cloud Run
• Serverless computing

Module 3: Google Kubernetes Engine and Containers

• Container fundamentals
• Google Kubernetes Engine (GKE)
• GKE architecture
• Cluster creation and management
• Nodes and workloads
• Deployments and services
• Kubernetes networking
• Autoscaling
• Container security
• Cloud Run and containerized applications

Module 4: Google Cloud Storage and Databases

• Cloud Storage
• Storage buckets
• Storage classes
• Object lifecycle management
• Persistent Disk
• Filestore
• Cloud SQL
• AlloyDB
• Firestore
• Bigtable
• Spanner
• Backup and recovery

Module 5: Google Cloud Networking

• Virtual Private Cloud (VPC)
• VPC networks
• Subnets
• IP addressing
• Routes
• Firewall rules
• Cloud Load Balancing
• Cloud DNS
• Cloud NAT
• VPC Peering
• Shared VPC
• Private Service Connect
• Cloud VPN
• Cloud Interconnect
• Cloud Router

Module 6: Identity, Access, and Security

• Google Cloud IAM
• Roles and permissions
• Service accounts
• Workload Identity
• Resource hierarchy
• Organization policies
• Authentication and authorization
• Encryption
• Cloud Key Management Service
• Secret Manager
• Security Command Center
• Cloud Armor
• VPC Service Controls
• Security best practices

Module 7: Data Analytics and Big Data

• BigQuery
• Data warehouses
• Data lakes
• Data ingestion
• Data processing
• BigQuery SQL
• Data visualization
• Data governance
• Pub/Sub
• Dataflow
• Dataproc
• Data analytics architectures

Module 8: Artificial Intelligence and Machine Learning

• AI and machine learning fundamentals
• Google Cloud AI services
• Vertex AI
• Generative AI
• Large language models
• AI application development
• Machine learning workflows
• Responsible AI
• AI security considerations
• Business applications of AI

Module 9: Monitoring and Cloud Operations

• Google Cloud Monitoring
• Cloud Logging
• Cloud Trace
• Cloud Profiler
• Error Reporting
• Metrics
• Logs
• Alerting policies
• Dashboards
• Application monitoring
• Infrastructure monitoring
• Troubleshooting

Module 10: DevOps and Application Deployment

• DevOps fundamentals
• Cloud Build
• Cloud Deploy
• Continuous Integration and Continuous Delivery
• Artifact Registry
• Source control
• Infrastructure as Code
• Deployment automation
• Application modernization
• Release management

Module 11: Cloud Architecture and Optimization

• Google Cloud architecture principles
• High availability
• Scalability
• Reliability
• Disaster recovery
• Business continuity
• Cost optimization
• Resource optimization
• Performance optimization
• Google Cloud Well-Architected Framework
• Sustainable cloud architecture

Module 12: Hands-On GCP Projects

• Create and configure a Google Cloud project
• Deploy Compute Engine workloads
• Configure VPC networking
• Deploy applications using Cloud Run
• Create a GKE environment
• Configure Cloud Storage
• Implement IAM policies
• Deploy a database solution
• Configure monitoring and alerts
• Secure cloud resources
• Troubleshoot a cloud deployment
• Optimize cloud resources

• Cloud Engineers
• Google Cloud Administrators
• Cloud Administrators
• System Administrators
• Network Engineers
• Cloud Architects
• Solutions Architects
• DevOps Engineers
• Site Reliability Engineers
• Software Developers
• Data Engineers
• Cybersecurity Professionals
• IT Infrastructure Professionals
• Students and Graduates interested in cloud computing
• IT professionals transitioning from on-premises infrastructure to cloud
• Professionals preparing for Google Cloud certifications

• Understand the fundamentals of Google Cloud Platform and cloud computing.
• Create and manage Google Cloud projects and resources.
• Deploy applications using Compute Engine, App Engine, Cloud Run, and GKE.
• Manage data using Cloud Storage and Google Cloud database services.
• Design and configure VPC networks, subnets, routes, and firewall rules.
• Implement hybrid connectivity using Cloud VPN and Cloud Interconnect.
• Manage identities and access using Google Cloud IAM.
• Secure cloud workloads using Cloud Armor, Security Command Center, encryption, and VPC Service Controls.
• Analyze data using BigQuery and Google Cloud data services.
• Understand Vertex AI and generative AI capabilities.
• Monitor cloud infrastructure using Cloud Monitoring and Cloud Logging.
• Implement DevOps and automated application deployment practices.
• Design highly available, scalable, reliable, and cost-effective cloud solutions.
• Troubleshoot and optimize Google Cloud workloads.
• Gain practical experience through hands-on GCP labs and projects.
• Build a foundation for advanced Google Cloud certifications and career paths.

• Basic understanding of IT infrastructure and cloud computing.
• Familiarity with operating systems and networking concepts.
• Basic understanding of virtual machines and storage.
• Familiarity with IP addressing, DNS, routing, and firewalls.
• Basic command-line knowledge is beneficial.
• Basic understanding of databases is helpful.
• Programming experience is beneficial for developer-focused modules but is not mandatory.
• No prior Google Cloud certification is required.

Course: Google Cloud Platform (GCP) Training
Training Level: Beginner to Advanced
Hands-On Training: Yes