ROI Training

Google Certified

Earn your certification. Boost your career.


Become a Google Certified Professional or Associate and show the world that you can design, develop, manage and administer application infrastructure and data solutions on Google Cloud technology. The Google Cloud Certified designation means you’ve demonstrated the necessary skills to leverage Google Cloud technology in a way that transforms businesses and meaningfully impacts the people and customers they serve.

√ Gain industry recognition.

√ Validate your technical expertise.

√ Take your career to the next level.


Cloud Architect

A Professional Cloud Architect enables organizations to leverage Google Cloud technologies. With a thorough understanding of cloud architecture and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.

The Google Cloud Certified – Professional Cloud Architect exam assesses your ability to:

  • Design and plan a cloud solution architecture
  • Manage and provision the cloud solution infrastructure
  • Design for security and compliance
  • Analyze and optimize technical and business processes
  • Manage implementations of cloud architecture
  • Ensure solution and operations reliability

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Data Engineer 

A Professional Data Engineer enables data-driven decision making by collecting, transforming, and visualizing data. The Data Engineer designs, builds, maintains, and troubleshoots data processing systems with a particular emphasis on the security, reliability, fault-tolerance, scalability, fidelity, and efficiency of such systems.

The Data Engineer also analyzes data to gain insight into business outcomes, builds statistical models to support decision-making, and creates machine learning models to automate and simplify key business processes.

The Google Cloud Certified – Professional Data Engineer exam assesses your ability to:

  • Build and maintain data structures and databases
  • Design data processing systems
  • Analyze data and enable machine learning
  • Model business processes for analysis and optimization
  • Design for reliability
  • Visualize data and advocate policy

Design for security and compliance

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