Top 6 Free GCP Programs 2021/2022 (Google Cloud Certification). This content is part of the Essential Guide on How to start your cloud career. The guide written below are the best 6 Google cloud certification programmes. The cloud work market continues to expand, but getting your resume to the top of the pile can be difficult. Consider obtaining one of these Google cloud certifications to set yourself apart from the competition.

Additional degrees and certifications have long been used by IT practitioners to set themselves apart. This is especially true of cloud computing, where new features and resources are introduced on a regular basis.

Company Managers usually use certifications as a guide to help them select the best choice for a job position. Google provides a number of cloud certification services, ranging from beginner to role-specific, for between $125 and $200.

There are no prerequisites for any of the certifications, but most suggest at least three years of business experience and at least one year of hands-on experience with Google Cloud Platform (GCP).

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In this article, we will examine the top Google certifications and the exams that go with them. We advise you to pay close attention to important links will you scroll down.

Top 6 Google Cloud Certification (GCP) Programs 2021

1. Associate Cloud Engineer (ACE)

Associate Cloud Engineer, which is the Google’s entry-level qualification programme, provides a single overall evaluation of the basic tasks required to use GCP. This course guarantees competency in the fundamentals of cloud operations, such as how to use the Google Cloud Console and command-line interface to build, instal, control, and protect an application.

An Associate Cloud Engineer Practitioner must understand the following:

  • account and billing setups;
  • simple component installations;
  • pricing calculator configurations;
  • compute, storage, and network resource selection;
  • resource control and management;
  • correct access and security configurations
  • and finally, full implementations using compute, Kubernetes, Google App Engine, and other GCP services.

This Google cloud certification programme necessarily involves approximately 26 weeks of hands-on training. Candidates will use the sample test and the free GCP tier to train.

2. Professional Cloud Architect (PCA)

An Architect for Cloud Computing: The Associate Cloud Engineer certification is an enhanced version of Google’s Professional Cloud Architect certification. The key distinction is that advanced principles are used, as well as a larger focus on market concerns. Many of the same topics are covered on both exams, such as architecture and management.

The following points are highlighted in this Google cloud certification programme:

  • designing, both from a commercial and technological standpoint;
  • establishing potential roadmaps and building relocation plans
  • computing and data provisioning and management
  • also designing for enforcement and security;
  • technical and market operations analysis and optimisation
  • for troubleshooting and reliability, as well as handling implementations and refining designs.

Recertification and resources

Candidates can use a range of tools from Google to help them train for the Associate and Professional tests, including an exam guide, a mock exam, and a free tier of practise skills. There are also opportunities for online and classroom instruction. These cloud certifications, on the other hand, must be renewed after two years. Recertification is especially useful in the cloud sector, where new technologies and upgrades to existing services are constantly being applied to each provider's menu of offerings.

3. Professional Cloud Developer (PCD)

Cloud Developer with Expertise: The cloud provides one-of-a-kind capabilities and tools to support a new wave of cloud-native computing applications. A candidate’s ability to build apps using Google’s managed services is validated by the Professional Cloud Developer qualification. The exam also covers the use of Google databases, runtimes, and tools, such as Stackdriver for tracking performance metrics.

Practitioners can learn how to do the following:

  • Create GCP applications and APIs using various programming methods, such as microservices;
  • Secondly, they will Ensure that the design process is secure;
  • Thirdly, practitioners can Organize and track application data
  • Finally, these practitioners can make preparations for device migrations.

The Professional Cloud Developer exam also covers:

  • Traditional test implementations and deployments in GCP services, such as App Engine and Cloud Functions;
  • integrations that link the application with other managed services, such as Cloud SQL;
  • and finally, application performance reporting, maintenance, and troubleshooting.

This cloud certification curriculum does not assess coding abilities or concentrate on a single programming language. You can click on the trending courses below.

4. Professional Cloud Network Engineer (PCNE)

A Professional Cloud Network Engineer’s Networks maintain sufficient capacity, low latency, and reliability. These are all essential for modern enterprise apps. The Professional Cloud Network Engineer certification from Google verifies a candidate’s ability to design, execute, maintain, and troubleshoot networks in Google Cloud Platform, including GCP Virtual Private Cloud (VPC).

The Professional Cloud Network Engineer tests & exam addresses the following topics:

  • The first step is to be able to network and design;
  • Secondly, they can master testing and deployment, including VPCs, routeing, firewalls, and Google Kubernetes Engine clusters;
  • and lastly, server load balancing, Cloud CDN, Cloud DNS, and other configurations.

Practitioners pursuing this Google cloud qualification programme must also be familiar with hybrid networking issues such as VLAN usage and bulk data transfers. Expect to learn more about identity and access management, Cloud Armor rules, integrating third-party devices into the virtual private server, and SSL key management in terms of encryption.

5. Professional Cloud Security Engineer (PCSE)

To insure adequate access, preserve business stability, safeguard confidential data, and satisfy regulatory enforcement criteria, businesses prioritise application protection. As more applications are migrated to the cloud, companies are paying closer attention to providers’ security services and settings, necessitating the recruiting of in-house cloud security specialists.

The Certified Cloud Security Engineer certification from Google assesses a candidate’s ability to plan and execute security in Google Cloud Platform (GCP) using a mix of best practises and GCP resources.

The Professional Cloud Security Engineer exam focuses on the following topics:

  • Authentication practises;
  • service account management;
  • data protection techniques;
  • resource hierarchies;
  • security ramifications of access through user account management;
  • resources and services such as Cloud Identification and Cloud Directory Sync.

Candidates will also research the security aspects of operations activities, such as infrastructure planning and execution, programme implementation, and incident tracking, as well as the compliance implications of protection of cloud infrastructures, for this particular Google cloud credential. Topics such as VPC networks and shared VPCs have some overlap with network security.

6. Professional Data Engineer (PDE)

The Certified Computer Engineer credential is designed to recognise IT professionals who work on data-intensive projects like big data, IoT, and machine learning. Finally, the PDE certificate and/or credential verifies a candidate’s ability to use GCP tools and facilities to collect, transform, process, and publish data.

Practitioners seeking this qualification must show their willingness to:

  • First of all, they can Plan data processing systems, including storage and computing elements;
  • Secondly, assemble systems using managed resources like Google BigQuery and Cloud Spanner;
  • Thirdly, develop and train machine learning models using services like AI Platform;
  • and lastly, insure stability, compliance, scalability, and performance.

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