Google Cloud Platform Course Syllabus

Introduction

Our Google cloud platform training in Chennai features an updated and comprehensive Google cloud platform course syllabus that would equip you with essential skills in cloud computing. With our Google cloud platform course syllabus, you can explore core GCP services like Kubernetes engine, compute engine, BigQuery, cloud architecture, security, and identity management.

With our Google cloud platform course syllabus, you can become proficient in advanced topics like machine learning and serverless computing. By utilizing our Google cloud platform course syllabus, you can become familiar with the deployment of scalable applications on GCP, optimization of cloud resources, and harnessing the power of data-driven insights for innovative solutions in real-world scenarios.

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Google cloud platform course syllabus

Module 1 – Introduction to Google Cloud Platform (GCP)

• Overview of GCP
• Registering on GCP: A guide for European users
• Exploring the Web Console: Understanding Projects and Billing
• Introduction to Cloud SDK

Module 2 – Identity & Access Management (IAM) on Google Cloud

• Overview of Google Cloud IAM
• Demonstrative Session: Adding an IAM Member
• Demonstrative Session: Creating a Custom Role
• Hierarchical Structure in IAM

Module 3 – Understanding Google Cloud Regions & Zones

• Overview of Regions and Zones on GCP

Module 4 – Google Cloud Virtual Machines

• Overview of Google Cloud’s Virtual Machine
• Demonstrative Session: Virtual Machines – Exploring Features
• GCP VM Images, Snapshots, and Cloning
• Demonstrative Session: Virtual Machines – Working with Images, Snapshots, and Cloning

Module 5 – Virtual Private Cloud (VPC) on Google Cloud

• Introduction to Networking and VPC on GCP
• Demonstrative Session: Setting up a VPC
• Demonstrative Session: Working with Multiple NICs on a VM
• VPC Peering and its Implementation
• Demonstrative Session: Establishing VPC Peering

Module 6 – Load Balancing and Autoscaling on Google Cloud

• Introduction to Load Balancers and Autoscaling in GCP
• Demonstrative Session: Implementing Load Balancing and Autoscaling

Module 7 – Content & Delivery Network (CDN) on Google Cloud

• Overview of Google Cloud’s CDN
• Understanding Cache Management in CDN
• Strategies to Monitor and Limit CDN Billing
• Demonstrative Session: Activating the CDN
• Demonstrative Session: Cache Management in CDN

Module 8 – Google Cloud Storage and Cloud SQL

• Introduction to Cloud Storage and Cloud SQL
• Features and Importance of Cloud SQL High Availability
• Demonstrative Session: Setting up and Connecting to Cloud SQL
• Demonstrative Session: Implementing Cloud SQL High Availability

Module 9 – Data Management with Cloud Datastore

• Introduction to Cloud Datastore and its Integration with Bigtable
• Understanding Consistency in Cloud Datastore
• Demonstrative Session: Working with Cloud Datastore
• Demonstrative Session: Entity Group Operations in Datastore

Module 10 – Exploring Cloud Spanner

• Overview of Cloud Spanner: Data Types and Models
• Demonstrative Session: Engaging with Spanner
• Demonstrative Session: Connecting to Spanner from Compute Engine

Module 11 – Networking –VPC

• Explain Regions, Zones, and Edge Locations
• Virtual Private Cloud
• Cloud Load Balancing
• Virtual Private Network

Module 12 – Deep Dive into Google Cloud Storage

• Introduction to Google Cloud’s Storage Solutions
• Exploring Storage Buckets and Objects
• Demonstrative Session: Using gsutil for Data Management

Module 13 – Virtual Machines

• Compute Engine
• Lab: Creating Virtual Machines
• Compute options (vCPU and Memory)
• Images
• Common Compute Engine actions
• Lab: Working with Virtual Machines

Module 14 – Autoscaling

• Autoscaling, Policies, Configuration
• Lab: Autoscaling

Module 15 – Load Balancing

• Managed Instance Groups
• HTTPS load balancing
• Cross-region and content-based load balancing
• SSL proxy/TCP proxy load balancing
• Network load balancing
• Lab: VM Automation and Load Balancing

Module 16 – Virtual Networks

• Virtual Private Cloud (VPC),
• Projects, Networks
• Subnetworks
• IP addresses
• Routes
• Firewall rules
• Subnetworks for resource management instead of physical network topology
• Lab: Virtual Networking
• Lab: Bastion Host

Module 17 – Interconnecting Networks

• Cloud Virtual Private Network (VPN)
• Lab: Virtual Private Networks (VPN)
• Cloud Router, Cloud Interconnect, External Peering, Cloud DNS

Module 18 – Cloud IAM

• Organizations
• Roles
• Members
• Service Accounts
• Cloud IAM best practices
• Lab: Cloud IAM

Module 19 – Data Storage Services

• Cloud Storage
• Lab: Cloud Storage
• Cloud SQL
• Lab: Cloud SQL
• Cloud Spanner, Cloud Datastore
• Cloud Bigtable

Module 20 – Resource Management

• Cloud Resource Manager
• Quotas
• Labels
• Names
• Billing
• Demo: Billing Administration
• Lab: Examining Billing Data with BigQuery

Module 21 – Resource Monitoring

• Stackdriver
• Monitoring
• Lab: Resource Monitoring (Stackdriver)
• Logging
• Error Reporting
• Tracing, Debugging
• Lab: Error Reporting and Debugging (Stackdriver)

Module 22 – Infrastructure Automation with Google Cloud Platform APIs

• Infrastructure automation
• Images
• Metadata
• Scripts
• Google Cloud API
• Lab: Google Cloud Platform API Infrastructure Automation

Module 23 – Infrastructure Automation with Deployment Manager

• Deployment Manager
• Configuration
• Cloud Launcher
• Lab: Deployment Manager

Module 24 – Storage & Database Services

• Cloud Storage
• Filestore
• Cloud SQL
• Cloud Spanner
• Cloud BigTable

Module 25 – Kubernetes –GKE

• Microservices architecture
• Containers
• Docker
• Google Kubernetes Engine (GKE)

Module 26 – Bigdata Solutions

• BigQuery
• Dataproc
• BigTable
• Dataflow
• Pub/Sub

Module 27 – Advanced Networking Topics

• Load balancing
• VPN

Module 28 – Management Tools (StackDriver)

• StackDriver logging
• StackDriver Monitoring

Module 29 – DevOps in GCP

• Jenkins with GCP
• Cloud Source Repository
• CI/CD with GCP
• Cloud Build

Module 30 – App Development & Deployment

• Google App Engine (GAE)
• Cloud Functions and Cloud Run
• CI/CD pipeline with Cloud Build and Cloud Source Repositories

Module 31 – Big Data and Analytics

• BigQuery: Data warehouse basics
• Dataflow, Dataproc, and Pub/Sub
• Real-time and batch data processing

Module 32 – Machine Learning and AI Services

• Introduction to AI and ML on GCP
• AutoML, Vertex AI, and Vision/NLP APIs
• Use cases and integration with data services

Module 33 – Monitoring, Logging, and Cost Management

• Cloud Monitoring (formerly Stackdriver)
• Logging, alerting, and error reporting
• Billing, budgeting, and cost optimization

Module 34 – Cloud Migrations

• Understanding Migration Used Cases
• Understanding Migration Tools and Process

Module 35 – Google Cloud BigQuery

• Introduction to BigQuery
• Loading data into BigQuery
• Querying data with SQL
• Data visualization and reporting
• BigQuery ML for machine learning models

Module 36 – Google Cloud Pub/Sub

• Introduction to Pub/Sub
• Creating topics and subscriptions
• Publishing and consuming messages
• Monitoring and logging
• Integrating Pub/Sub with other GCP services

Module 37 – Storage and Database services in GCP

• Cloud SQL
• Cloud Spanner
• Cloud Datastore
• Cloud Bigtable
• Tradeoff of storage options
• Integration with multi-cloud environment

Module 38 – Containers

• Learn containers and their benefits
• Usage of kubernetes engine
• How to choose Containers on compute engine

Module 39 – Cloud dataflow for Data Processing

• Dataflow service
• Data transformation with cloud data flow
• Using Stack driver for Monitoring
• Learn to create cluster
• Job Automation

Module 40 – GCP APIs and Development Services

• Automate the Infrastructure, Scripts, Google cloud API
• API Management
• Learn to use Google stackdriver
• App Engine

Module 41 – GCP Devops services

• Make a setup on CI/CD
• Setting up Jenkins on container engine
• Try to Create and deploy on cluster

Module 42 – Designing and implementing GCP Migration

• Different critical metrics and analytics
• Migrate to GCP
• Hybrid model
• How to manage scalability

• Different critical KPIs, Metrics, Analytics
• How to take decision to migrate to GCP
• How to choose from different options as per specific need
• How to manage scalability
• Hybrid model
• How to move completely from on-prem to GCP

• Collect and Analyze metrics
• Evaluate and choose an automation framework for provisioning resources in cloud
• Design strategy
• Create Migration Plan
• Move local data to GCP

Conclusion

Our Google cloud platform course in Chennai provides a comprehensive Google cloud platform course syllabus that covers a wide range of important topics to equip you with practical skills for cloud computing.

Our Google cloud platform course syllabus starts with basic concepts like cloud architecture and service models (IaaS, PaaS, Saas) and gradually proceeds to advanced topics like networking, data management techniques, and security best practices.

Our Google cloud platform course syllabus also includes hands-on training in key services like cloud storage, compute engine, and BigQuery. With our Google cloud platform course syllabus, you can become proficient in using automation tools like Kubernetes and Cloud Functions.

By utilizing our Google cloud platform course syllabus, you can also explore machine learning integration, advanced analytics, and the effective use of Google APIs. By the end of the Google cloud platform training program in Chennai, you will be well-equipped to manage and deploy scalable applications in the cloud.

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