Best Software Training Institute in Hyderabad – Version IT

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📅 Course Duration

2 Months

💰 Course Price

₹ 25000

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📄 Course Content

GCP Data Engineer Training in Vizag

Google Cloud Platform (GCP) is among the technologies that are most rapidly developing in cloud computing. Various companies require data engineers who are capable of processing, managing, and analysing huge amounts of data on the cloud. Whether you’re a student, working professionals from Vizag or from any place, Version IT provides a full GCP Data Engineer Training Program online. Our course provides knowledge of how to design pipelines of data, operate data warehouses, and create end-to-end data solutions using GCP services.

Why Choose GCP Data Engineering?

Data engineering has become an essential requirement of the digital economy. Companies rely on accurate data information in decision-making. The services offered by GCP, which are BigQuery, Dataflow, Pub/Sub and Dataproc can help provide scalable solutions to the businesses of the current era.

A certified GCP Data Engineer can:

  • Establish and gain confidence in sound data processing systems.
  • Create real-time and batch data pipelines.
  • Fuel decision-making using smart analytics.
  • Reduce expenses through optimization of cloud architecture.

Your future career as a GCP Data Engineer will enable you to work in a live cloud environment and this is achievable by attending best GCP Data Engineer Training in Vizag.

About Version IT’s GCP Data Engineer Online Training in Vizag

Version It is one of the top GCP Data Engineer Training Institute. We are trained according to the most recent Google Cloud Professional Data engineer certification model. It is constructed on practical education through live projects hence you will be a completed course person with job-ready skills.

The highlights of our GCP Data Engineer training program are as follows:

– GCP qualified professionals that introduce practical experience.

– Hands-on activities and collaborative laboratories to support learning.

– Preparation guide to the exam Google Professional Data Engineer.

– Placement support and career guidance of the students and professionals.

Whether it is the first time you are introduced to cloud computing or you are an IT expert and wish to upgrade to be a successful data engineer in GCP, this course provides a straightforward map of becoming an effective one.

GCP Data Engineer Course Skills You Will Learn

Through our training, you will acquire the knowledge of the theoretical and practical side of GCP data engineering. You will get to know how to:

  • Navigate the Google Cloud Platform and its console
  • Use BigQuery to warehouse and query
  • Create ETL pipelines in Cloud Dataflow and Dataproc
  • Process real-time data in Pub/SUB and Data Fusion
  • Manage data in Cloud Storage with advanced partitioning
  • Deploy machine-learning models in BigQuery ML
  • Manage IAM roles, and how to optimize performance and control costs.

These are skills that will equip you with complex data-engineering situations in the modern business world.

Topics You will Learn

Introduction to Google Cloud Platform

● Google Cloud Platform (GCP) Infrastructure
● Using GCP
● Lab: Console and Cloud Shell
● Demo: Projects
● Lab: Infrastructure Preview

Virtual Machines

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

Autoscaling

● Autoscaling, Policies, Configuration
● Lab: Autoscaling

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

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

Interconnecting Networks

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

Cloud IAM

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

Data Storage Services

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

Resource Management

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

Resource Monitoring

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

Infrastructure Automation with Google Cloud Platform APIs

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

Infrastructure Automation with Deployment Manager

● Deployment Manager
● Configuration
● Cloud Launcher
● Lab: Deployment Manager

Let Your Certificates Speak

All You Need to Start this Course

FAQ's

The course will prepare you to create scalable data pipelines, operate with large-scale data on Google Cloud, and create machine-learning models. You will use the fundamental services like BigQuery, Dataflow and Cloud Dataproc to build end to end solutions.

The target market of this training is on IT graduates, working professionals and data analysts. It can also be used by anyone who wishes to start a cloud-based data engineering career by using Google Cloud technologies.

Majority of the institutes include specific course of Google Cloud Professional Data Engineer exam preparation in their curriculum and cover all major topics to pass exam.

Yes, the course work will feature on-the-job projects and working lab sessions. Students are exposed to working with, processing, and analyzing big data using Google Cloud solutions.

GCP Data Engineers are also demanded highly. Professional opportunities encompass cloud migration, data pipeline development, and analytics projects in major companies.

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