• If you’re in dilemma and thinking how to grow in your career, then you are at the right place. Today, where the competition is high and everyone is looking forward to how to make a handsome amount of money is looking for various career options.
  • To make people aspire their dreams to get a well-established career is Google Cloud Certification Training Program. In our program you get the basic knowledge to the advanced level and get a training certification as well. We prepare you to be a qualified candidate with all the skills.
  • The Google Cloud Certification Training Program offered by us created by the industry experts to meet the industry standards. All the individuals have given their many years to the industry and today they have their own expertise to guide students to fulfil their dreams through this course.
  • Once you decide to choose our Google Cloud Training Program in Gurgaon then you get an opportunity to build a strong foundation in the Google Cloud Space. You get to learn everything from managing, designing, developing and deploying high-quality cloud solutions in less time than required during your Google cloud training in Gurgaon. We make you practice via the project work, assignments, and assessments to elevate your skills.
  • You get to dive deep into the knowledge of Google Cloud Platform. You become a knowledgeable person in managing various GCP services starting from database services, networking concepts, security concepts, and more. With us you get quality study and convenience as you choose our Google Cloud Placement Course. So, you can think of getting full assistance till you land to a high-paying job.

Google Cloud Training in Gurgaon


  • Course Objectives:
    • In our Google Cloud Training Program in Gurgaon, you get to learn the Google Cloud Fundamentals, Networking, Storage Services, tools, AI Services, Operations and more.

      You get to understand Google Cloud Platform thoroughly and become proficient enough to give the commands. You become successful in working with Command line tools, Google Cloud, G suite and more.

      You get an understanding of detailed designing of statics or dynamic cloud routes. An idea of GCP firewalls, how to make use of or implement VPC peering concepts.

      A deep knowledge of handling or managing traffic with the help of auto scale concepts, while how to set IAM policy at multi-levels. You get an understanding of how to demonstrate VMs or compute engine when required.

      Our Google Cloud Certification Training in Gurgaon gives you an idea of Kubernetes cluster, App engine, Cloud logging, Cloud monitoring, Cloud repository and much more.

      An understanding of how to manage the provisions of Google cloud solutions; know about various GCP products, run data queries, machine learning services and more.

  • Planning out your career is essential but choosing a course with high-paying salary is necessity. Coming across all the ins and outs is essential. Likewise, when opting for Google Cloud Certification Training in Gurgaon satiate your thoughts related to salary expectations. So, for your better clarification Google Cloud offer three different cloud services. Expanding your career and creating plenty of opportunities is what come hand-in-hand with us. You create plenty of opportunities for yourself when enrolling with us.
  • We will help you with the resume building, career guidance, tips to crack the interview and much more. Our Google Cloud Certification training is not just limited to knowledge. You get a proof of your skills too. With us you get an average salary of $128k annually once you become a Google Cloud Professional. To get yourself enrolled in our Google Cloud Training Program you avail high paying salaries meeting all your expectations.

  • Career Growth After Course:
    • With our Google Cloud Certification Training you get to skyrocket your career and you get to grow fulfilling your needs.

      Every other industry is expanding at an alarming rate which will definitely increase the job options. Once having the right skills, you become a part of the evergreen career with huge chances of growth.

      You will get to prepare with all the basic and advanced knowledge of various concepts helping you execute at the workplace. With all the right skills you become highly knowledgeable cracking your exam in one shot.

      In our Google Cloud Training Program, you become in proficient in working on the LIVE projects. You get to become industry ready opening never-ending career growth options.

  • In the IT world or we would better worldwide Google is a big and common name. Google is a big giant in the business world and ruling the world with its services and products. Google Cloud which is a product of Google that helps you to make data store securely in comparison to other cloud platforms. This is the reason the demand for Google Cloud certified professionals is at peak and is expected to grow with the passage of time.
  • With various benefits Google Cloud is helping other companies in managing the data as well as making them save the overall space. To clear the Google Cloud certification exam is a big achievement and should not be missed anyhow.
  • Google Cloud Certification proves to be a boon in multiple ways. In our Google Cloud Placement Course, you get hands-on training and learn the designing and deployment of Google Cloud Solutions for enterprises.

  • Our Google Cloud Training Course in Gurgaon you get the right knowledge which makes you fulfil all your roles and responsibilities at the workplace.
    • Complete understanding of GCP Services, Google Cloud Fundamentals, Storage Services, Tools, Operations and AI Services

      Understanding of how to manage Google Cloud Platform and command line on the fingertips

      Knowledge of how to work with Command line tools, G suite, Google Cloud and more

      A detailed understanding for designing dynamic and static cloud routes while having an understanding of implementation of VPC peering concepts and GCP firewalls

      Traffic management with auto scale concepts and IAM policy on different various levels with an understanding of demonstration of compute engine or VMS whenever required

      Familiar with Kubernetes cluster, App engine, Data usage, cloud logging, cloud repository, cloud monitoring services and more

      Complete understanding of how to manage or provision the Google Cloud Solutions, GCP products, GCP services, data queries, machine learning services, Google Cloud Architecture and more

  • With the complete knowledge in our Google Cloud Training Institute in Gurgaon, we make you a resourceful skill to outperform the roles and responsibilities with full confidence.

  • Our industry experts have designed Google Cloud Training Program in Gurgaon in such a way that you get complete knowledge while preparing yourself for the various job opportunities in the leading industries. You get a chance to shape your career beautifully as you get to practice on the assignments, case studies, projects effortlessly. With the help of quizzes and assessments you evaluate your skills.
  • The Google Cloud Placement Course makes you a master with the right skills and become a part of popular companies like Genpact, Hexaware, Cisco, IBM, TCS and many more. While practicing you become an efficient resource which helps you earn a lot of bucks.

  • Earn all the Google Cloud Platform skills with our Google Cloud Certification Program and become a part of journey with full of amazing opportunities. With full determination, we help you kick start your career by passing all the necessary certifications which helps you to boost your resume. You get to take a step forward in the Cloud industry while expanding career growth in the leading industries.
  • After the successful completion of Google Cloud Certification Training in Gurgaon, you will complete your project work and assessment which will help you become eligible with a certification that is globally accepted. You can show your certification after Google cloud training institute in Gurgaon as a proof of your skills. So, what awaits you for more to fly high in the cloud industry Speak to our industry experts now.

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Google Cloud Certification Training Programs

Google Cloud Certification TrainingPrograms

Google Cloud
Google Cloud-Associate Cloud Engineer
30k LearnersWeekend/WeekdayLive Class
  • 2 Live Project
  • Self-Paced/ Classroom
  • Certification Pass Guaranteed

  • Setting up cloud projects and accounts. Activities include
    • Creating projects

      Assigning users to predefined IAM roles within a project

      Managing users in Cloud Identity (manually and automated)

      Enabling APIs within projects

      Provisioning one or more Stackdriver workspaces

  • Managing billing configuration. Activities include
    • Creating one or more billing accounts

      Linking projects to a billing account

      Establishing billing budgets and alerts

      Setting up billing exports to estimate daily/monthly charges

  • Installing and configuring the command line interface (CLI), specifically the Cloud SDK (e.g., setting the default project)
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  • Planning and estimating GCP product use using the Pricing Calculator
  • Planning and configuring compute resources. Considerations include
    • Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine, App Engine, Cloud Run, Cloud Functions)

      Using preemptible VMs and custom machine types as appropriate

  • Planning and configuring data storage options. Considerations include
    • Product choice (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Bigtable)

      Choosing storage options (e.g., Standard, Nearline, Coldline, Archive)

  • Planning and configuring network resources. Tasks include
    • Differentiating load balancing options

      Identifying resource locations in a network for availability

      Configuring Cloud DNS

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  • Deploying and implementing Compute Engine resources. Tasks include
    • Launching a compute instance using Cloud Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)

      Creating an autoscaled managed instance group using an instance


      Generating/uploading a custom SSH key for instances

      Configuring a VM for Stackdriver monitoring and logging

      Assessing compute quotas and requesting increases

      Installing the Stackdriver Agent for monitoring and logging

  • Deploying and implementing Google Kubernetes Engine resources. Tasks include
    • Deploying a Google Kubernetes Engine cluster

      Deploying a container application to Google Kubernetes Engine using pods

      Configuring Google Kubernetes Engine application monitoring and logging

  • Deploying and implementing App Engine, Cloud Run, and Cloud Functions resources. Tasks include, where applicable
    • Deploying an application, updating scaling configuration, versions, and traffic splitting

      Deploying an application that receives Google Cloud events (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)

  • Deploying and implementing data solutions. Tasks include
    • Initializing data systems with products (e.g., Cloud SQL, Cloud Data store, BigQuery, Cloud Spanner, Cloud Pub/Sub, Cloud Bigtable, Cloud Dataproc, Cloud Dataflow, Cloud Storage)

      Loading data (e.g., command line upload, API transfer, import/export, load data from Cloud Storage, streaming data to Cloud Pub/Sub)

  • Deploying and implementing networking resources. Tasks include
    • Creating a VPC with subnets (e.g., custom-mode VPC, shared VPC)

      Launching a Compute Engine instance with custom network configuration (e.g., internal-only IP address, Google private access, static external and private IP address, network tags)

      Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, tags, service accounts)

      Creating a VPN between a Google VPC and an external network using Cloud VPN

      Creating a load balancer to distribute application network traffic to an application (e.g., Global HTTP(S) load balancer, Global SSL Proxy load balancer, Global TCP Proxy load balancer, regional network load balancer, regional internal load balancer)

  • Deploying a solution using Cloud Marketplace. Tasks include
    • Browsing Cloud Marketplace catalog and viewing solution details

      Deploying a Cloud Marketplace solution

  • Deploying application infrastructure using Cloud Deployment Manager. Tasks include
    • Developing Deployment Manager templates

      Launching a Deployment Manager template

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  • Managing Compute Engine resources. Tasks include
    • Managing a single VM instance (e.g., start, stop, edit configuration, or delete an instance)

      SSH/RDP to the instance

      Attaching a GPU to a new instance and installing CUDA libraries

      Viewing current running VM inventory (instance IDs, details)

      Working with snapshots (e.g., create a snapshot from a VM, view snap shots, delete a snapshot)

      Working with images (e.g., create an image from a VM or a snapshot, view images, delete an image)

      Working with instance groups (e.g., set autoscaling parameters, assign instance template, create an instance template, remove instance group)

      Working with management interfaces (e.g., Cloud Console, Cloud Shell, GCloud SDK)

  • Managing Google Kubernetes Engine resources. Tasks include
    • Viewing current running cluster inventory (nodes, pods, services)

      Working with node pools (e.g., add, edit, or remove a node pool)

      Working with pods (e.g., add, edit, or remove pods)

      Working with services (e.g., add, edit, or remove a service)

      Working with stateful applications (e.g. persistent volumes, stateful sets)

      Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

  • Managing Google Kubernetes Engine resources. Tasks include
    • Viewing current running cluster inventory (nodes, pods, services)

      Working with node pools (e.g., add, edit, or remove a node pool)

      Working with pods (e.g., add, edit, or remove pods)

      Working with services (e.g., add, edit, or remove a service)

      Working with stateful applications (e.g. persistent volumes, stateful sets)

      Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

  • Managing App Engine and Cloud Run resources. Tasks include
    • Adjusting application traffic splitting parameters

      Setting scaling parameters for autoscaling instances

      Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

  • Managing storage and database solutions. Tasks include
    • Moving objects between Cloud Storage buckets

      Converting Cloud Storage buckets between storage classes

      Setting object life cycle management policies for Cloud Storage buckets

      Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Datastore, Cloud Bigtable)

      Estimating costs of a BigQuery query

      Backing up and restoring data instances (e.g., Cloud SQL, Cloud Datastore)

      Reviewing job status in Cloud Dataproc, Cloud Dataflow, or BigQuery

      Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

  • Managing networking resources. Tasks include
    • Adding a subnet to an existing VPC

      Expanding a subnet to have more IP addresses

      Reserving static external or internal IP addresses

      Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK

  • Monitoring and logging. Tasks include
    • Creating Stackdriver alerts based on resource metrics

      Configuring log sinks to export logs to external systems (e.g., on-premises or BigQu

      Viewing specific log message details in Stackdriver

      Using cloud diagnostics to research an application issue (e.g., viewing Cloud Trace data, using Cloud Debug to view an application point-in-time)

      Viewing Google Cloud Platform status

      Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

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  • Managing identity and access management (IAM). Tasks include
    • Viewing IAM role assignments

      Assigning IAM roles to accounts or Google Groups

      Defining custom IAM roles

  • Managing service accounts. Tasks include
    • Managing service accounts with limited privileges

      Assigning a service account to VM instances

      Granting access to a service account in another project

  • Viewing audit logs for project and managed services.
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Google Cloud
Google Cloud-Professional Cloud Architect
30k LearnersWeekend/WeekdayLive Class
  • 2 Live Project
  • Self-Paced/ Classroom
  • Certification Pass Guaranteed

  • Designing a solution infrastructure that meets business requirements. Considerations include
    • Business use cases and product strategy

      Cost optimization

      Supporting the application design

      Integration with external systems

      Movement of data

      Design decision trade-offs

      Build, buy, or modify

      Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)

      Compliance and observability

  • Designing a solution infrastructure that meets technical requirements. Considerations include
    • High availability and failover design

      Elasticity of cloud resources

      Scalability to meet growth requirements

      Performance and latency

  • Designing network, storage, and compute resources. Considerations include
    • Integration with on-premises/multi-cloud environments

      Cloud-native networking (VPC, peering, firewalls, container networking)

      Choosing data processing technologies

      Choosing appropriate storage types (e.g., object, file, RDBMS, NoSQL, New SQL)

      Choosing compute resources (e.g., pre-emptible, custom machine type, specialized workload)

      Mapping compute needs to platform products

  • Creating a migration plan (i.e., documents and architectural diagrams). Considerations include
    • Integrating solution with existing systems

      Migrating systems and data to support the solution

      Licensing mapping

      Network planning

      Testing and proof of concept

      Dependency management planning

  • Envisioning future solution improvements. Considerations include
    • Cloud and technology improvements

      Business needs evolution

      Evangelism and advocacy

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  • Configuring network topologies. Considerations include
    • Extending to on-premises (hybrid networking)

      Extending to a multi-cloud environment that may include GCP to GCP communication

      Security and data protection

  • Configuring individual storage systems. Considerations include
    • Data storage allocation

      Data processing/compute provisioning

      Security and access management

      Network configuration for data transfer and latency

      Data retention and data life cycle management

      Data growth management

  • Configuring compute systems. Considerations include
    • Compute system provisioning

      Compute volatility configuration (preemptible vs. standard)

      Network configuration for compute nodes

  • Infrastructure provisioning technology configuration (e.g. Chef/Puppet/Ansible/Terraform/Deployment Manager)
  • Container orchestration with Kubernetes
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  • Designing for security. Considerations include
    • Identity and access management (IAM)

      Resource hierarchy (organizations, folders, projects)

      Data security (key management, encryption)

      Penetration testing

      Separation of duties (SoD)

      Security controls (e.g., auditing, VPC Service Controls, organization policy)

      Managing customer-managed encryption keys with Cloud KMS

  • Designing for compliance. Considerations include
    • Legislation (e.g., health record privacy, childrens privacy, data privacy, and ownership)

      Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])

      Industry certifications (e.g., SOC 2)

      Audits (including logs

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  • Analyzing and defining technical processes. Considerations include
    • Software development life cycle plan (SDLC)

      Continuous integration / continuous deployment

      Troubleshooting / post mortem analysis culture

      Testing and validation

      Service catalogue and provisioning

      Business continuity and disaster recovery

  • Analyzing and defining business processes. Considerations include:
    • Stakeholder management (e.g. influencing and facilitation)

      Change management

      Team assessment / skills readiness

      Decision-making process

      Customer success management

      Cost optimization / resource optimization (capex / opex)

  • Developing procedures to ensure resilience of solution in production (e.g., chaos engineering)
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  • Advising development/operation team(s) to ensure successful deployment of the solution. Considerations include
    • Application development

      API best practices

      Testing frameworks (load/unit/integration)

      Data and system migration tooling

  • Interacting with Google Cloud using GCP SDK (gcloud, gsutil, and bq). Considerations include
    • Local installation

      Google Cloud Shell

  • IAM user- groups
    • Creating a user and group

      Adding a user to the group

      Password policy setup for users

      Attaching policy to users

      Enabling dual /Multifactor authentication to the users

  • IAM Roles
    • Creating a role

      Launching a EC2 instance using a S3 full access role

      Deleting a role

  • Security Token service
  • Security on AWS
  • AWS and IT audits
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Google Cloud
Google Cloud-Professional Cloud DevOps Engineer
30k LearnersWeekend/WeekdayLive Class
  • 2 Live Project
  • Self-Paced/ Classroom
  • Certification Pass Guaranteed

  • Balance change, velocity, and reliability of the service
    • Discover SLIs (availability, latency, etc.)

      Define SLOs and understand SLAs

      Agree to consequences of not meeting the error budget

      Construct feedback loops to decide what to build next

      Toil automation

  • Manage service life cycle
    • Manage a service (e.g., introduce a new service, deploy it, maintain and retire it)

      Plan for capacity (e.g., quotas and limits management)

  • Ensure healthy communication and collaboration for operations
    • Prevent burnout (e.g., set up automation processes to prevent burnout)

      Foster a learning culture

      Foster a culture of blamelessness

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  • Design CI/CD pipelines
    • Immutable artifacts with Container Registry

      Artifacts repositories with Container Registry

      Deployment strategies with Cloud Build, Spinnaker

      Deployment to hybrid and multi-cloud environments with Anthos, Spinnaker, Kubernetes

      Artifacts versioning strategy with Cloud Build, Container Registry

      CI/CD pipeline triggers with Cloud Source Repositories, Cloud Build GitHub App, Cloud Pub/Sub

      Testing a new version with Spinnaker

      Configure deployment processes (e.g., approval flows

  • Implement CI/CD pipelines
    • CI with Cloud Build

      CD with Cloud Build

      Open source tooling (e.g. Jenkins, Spinnaker, Git Lab, Concourse)

      Auditing and tracing of deployments (e.g., CSR, Cloud Build, Cloud Audit Logs)

  • Manage configuration and secrets
    • Secure storage methods

      Secret rotation and configuration changes

  • Manage infrastructure as code
    • Terraform / Cloud Deployment Manager

      Infrastructure code versioning

      Make infrastructure changes safer

      Immutable architecture

  • Deploy CI/CD tooling
    • Centralized tools vs. multiple tools (single vs multi-tenant)

      Security of CI/CD tooling

  • Manage different development environments (e.g., staging, production, etc.):
    • Decide on the number of environments and their purpose

      Create environments dynamically per feature branch with GKE, Cloud Deployment Manager

      Local development environments with Docker, Cloud Code, Scaffold

  • Secure the deployment pipeline:
    • Vulnerability analysis with Container Registry

      Binary Authorization

      IAM policies per environment

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  • Manage application logs
    • Collecting logs from Compute Engine, GKE with Stackdriver Logging, Fluentd

      Collecting third-party and structured logs with Stackdriver Logging, Fluentd

      Sending application logs directly to Stackdriver API with Stackdriver Logging

  • Manage application metrics with Stackdriver Monitoring
    • Collecting metrics from Compute Engine

      Collecting GKE/Kubernetes metrics

      Use metric explorer for ad hoc metric analysis

  • Manage Stackdriver Monitoring platform
    • Creating a monitoring dashboard

      Filtering and sharing dashboards

      Configure third-party alerting in Stackdriver Monitoring (i.e., Pager Duty, Slack, etc.)

      Define alerting policies based on SLIs with Stackdriver Monitoring

      Automate alerting policy definition with Cloud DM or Terraform

      Implementing SLO monitoring and alerting with Stackdriver Monitoring

      Understand Stackdriver Monitoring integrations (e.g., Grafana, BigQuery)

      Using SIEM tools to analyze audit/flow logs (e.g., Splunk, Data dog)

      Design Stackdriver Workspace strategy

  • Manage Stack Driver Logging platform
    • Enabling data access logs (e.g., Cloud Audit Logs)

      Enabling VPC flow logs

      Viewing logs in the GCP Console

      Using basic vs. advanced logging filters

      Implementing logs-based metrics

      Understanding the logging exclusion vs. logging export

      Selecting the options for logging export

      Implementing a project-level / org-level export

      Viewing export logs in Cloud Storage and BigQuery

      Sending logs to an external logging platform

  • Implement logging and monitoring access controls:
    • Set ACL to restrict access to audit logs with IAM, Stack driver Logging

      Set ACL to restrict export configuration with IAM, Stack driver Logging

      Set ACL to allow metric writing for custom metrics with IAM, Stack driver Monitoring

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  • Identify service performance issues
    • Evaluate and understand user impact (Stackdriver Service Monitoring for App Engine, Istio)

      Utilize Stackdriver to identify cloud resource utilization

      Utilize Stackdriver Trace/Profiler to profile performance characteristics

      Interpret service mesh telemetry

      Troubleshoot issues with the image/OS

      Troubleshoot network issues (e.g., VPC flow logs, firewall logs, latency, view network details)

  • Debug application code:
    • Application instrumentation

      Stackdriver Debugger

      Stackdriver Logging

      Stackdriver Trace

      Debugging distributed applications

      App Engine local development server

      Stackdriver Error Reporting

      Stackdriver Profiler

  • Optimize resource utilization:
    • Identify resource costs

      Identify resource utilization levels

      Develop plan to optimize areas of greatest cost or lowest utilization

      Manage pre-emptible VMs

      Work with committed-use discounts

      TCO considerations

      Consider network pricing

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  • Coordinate roles and implement communication channels during a service incident:
    • Define roles (incident commander, communication lead, operations lead)

      Handle requests for impact assessment

      Provide regular status updates, internal and external

      Record major changes in incident state (When mitigated When all clear etc.)

      Establish communications channels (email, IRC, Hangouts, Slack, phone, etc.)

      Scaling response team and delegation

      Avoid exhaustion / burnout

      Rotate / hand over roles

      Manage stakeholder relationships

  • Investigate incident symptoms impacting users
    • Identify probable causes of service failure

      Evaluate symptoms against probable causes; rank probability of cause based on observed behavior

      Perform investigation to isolate most likely actual cause

      Identify alternatives to mitigate issue

  • Mitigate incident impact on users:
    • Roll back release

      Drain / redirect traffic

      Turn off experiment

      Add capacity

  • Resolve issues (e.g., Cloud Build, Jenkins):
    • Code change / fix bug

      Verify fix

      Declare all-clear

  • Document issue in a post-mortem:
    • Document root causes

      Create and prioritize action items

      Communicate post-mortem to stakeholders

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Google Cloud
Google Cloud-Professional Data Engineer
30k LearnersWeekend/WeekdayLive Class
  • 2 Live Project
  • Self-Paced/ Classroom
  • Certification Pass Guaranteed

  • Data processing Fundamentals
    • Data Processing Concepts

      Data Processing Pipelines

  • Data Storage Fundamentals
    • About GCP

      Data Storage in GCP

      Working with Data

      Cloud Storage

      Data Transfer Services

      Cloud Fire Store

      Cloud Spanner

      Cloud Memory Store

      Different Memory options

  • Selecting the best memory storage
    • Compare storage options

      Mapping storage systems to business requirements

      Data modeling

      Trade-offs involving latency, throughput, transactions

      Distributed systems

      Schema design

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  • Data publishing and visualization
  • Online (interactive) vs. batch predictions
  • Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
  • Big Data Ecosystem
    • MapReduce

      Hadoop & HDFS

      Apache Pig

      Apache Spark

      Apache Kafka

  • Real-time Messaging with Pub/Sub
    • Pub/sub basics

      pub/Sub Terminologies

      Advanced Pub/Sub Concepts

      Working with Pub/Sub

  • Cloud Data Flow Pipelining
    • Dataproc Basics

      Working with Dataproc

      Advanced Dataproc

  • NoSQL Data with Cloud Big Table
    • Big Table Concepts

      Big Table Architecture

      Big Table Data Model

      Big Table Schema Design

      Big Table Advanced Concepts

  • Data Analytics using BigQuery
    • BigQuery Basics

      Using BigQuery

      Partitioning and Clustering

      Best Practices

      Securing BigQuery

      BigQuery Monitoring and Logging

      Machine Learning with BigQuery ML

      Working with BigQuery

      Advanced BigQuery Concepts

  • Data Exploration with Cloud Datalab
    • Datalab Concepts

      Working with Datalab

  • Visualization with Cloud Data Studio
    • Reporting & Business intelligence

      Data Distribution

      Introduction to Cloud Data Studio

      Charts and Filters

  • Job automation and orchestration (e.g., Cloud Composer)
    • Orchestration with Cloud Composer

      Cloud Composer Overview

      Cloud Composer Architecture

      Working with Cloud Composer

      Advanced Cloud Composer Concepts

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  • Steps for Designing
    • Choice of infrastructure

      System availability and fault tolerance

      Use of distributed systems

      Capacity planning

      Hybrid cloud and edge computing

      Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)

      At least once, in-order, and exactly once, etc., event processing

  • Migrating data warehousing and data processing
    • Awareness of current state and how to migrate a design to a future state

      Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)

      Validating a migration

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  • Building and operationalizing Storage Solutions
    • Cloud Managed Services

      Effectives Use of Managed Services

      Storage Cost and performance

      Lifecycle Management of Data

  • Building and operationalizing Pipelines
    • Data cleansing

      Batch and streaming


      Data acquisition and import

      Integrating with new data sources

  • Building and operationalizing processing infrastructure
    • Provisioning resources

      Monitoring pipelines

      Adjusting pipelines

      Testing and quality control

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  • Introduction to Machine Learning
    • Machine Learning Introduction

      Machine Learning Basics

      Machine Learning Types and Models



      Feature Engineering

  • Machine Learning with TesnorFlow
    • Deep Learning with TensorFlow

      Introduction to Artificial Neural Networks

      Neural Network Architectures

      Building a Neural Network

  • Leveraging pre-built ML models as a service. Considerations include:
    • ML APIs (e.g., Vision API, Speech API)

      Customizing ML APIs (e.g., AutoML Vision, Auto ML text)

      Conversational experiences (e.g., Dialogflow)

  • Deploying an ML pipeline
    • Ingesting appropriate data

      Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)

      Continuous evaluation

  • Choosing the appropriate training and serving infrastructure
    • Distributed vs. single machine

      Use of edge compute

      Hardware accelerators (e.g., GPU, TPU)

  • Measuring, monitoring, and troubleshooting machine learning models
    • Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)

      Impact of dependencies of machine learning models

      Common sources of error (e.g., assumptions about data)

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Prepare & Practice for real-life job interviews by joining the Mock Interviews drive at Croma Campus and learn to perform with confidence with our expert team.Not sure of Interview environments? Don’t worry, our team will familiarize you and help you in giving your best shot even under heavy pressures.Our Mock Interviews are conducted by trailblazing industry-experts having years of experience and they will surely help you to improve your chances of getting hired in real.How Croma Campus Placement Process Works?


Validate your skills and knowledge by working on industry-based projects that includes significant real-time use cases.Gain hands-on expertize in Top IT skills and become industry-ready after completing our project works and assessments.Our projects are perfectly aligned with the modules given in the curriculum and they are picked up based on latest industry standards.Add some meaningful project works in your resume, get noticed by top industries and start earning huge salary lumps right away.
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No, the concepts are not too sophisticated and individuals can easily get out an overview of concepts. However, it needs the effective dedication of candidates.

While during the course period of Google Cloud Training in Gurgaon you get to know various certifications. While in today’s environment “Associate” get considered as best.

There are multiple reasons for selecting Croma Campus for the Google Cloud course. We are considering the main ones through the below-mentioned details:

  • Personalized doubt clearing session.
  • Structured course material.
  • Corporate instructors.

Yes, after completing your course at Google Cloud Training Institute in Gurgaon you can quickly get out job according to your expectations.

With the gaining popularity of GCP in the cloud computing market professionals, as well as new candidates, are elaborating on it.

Career Assistancecareer assistance
  • - Build an Impressive Resume
  • - Get Tips from Trainer to Clear Interviews
  • - Attend Mock-Up Interviews with Experts
  • - Get Interviews & Get Hired
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