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Real-time code analysis and feedback
Course Description
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.
It is a continuation of the Architecting with Google Cloud Platform: Infrastructure course and assumes hands-on experience with the technologies covered in that course. Through a combination of presentations, demos, and hands-on labs, participants learn to design GCP deployments that are highly reliable and secure; and how to operate GCP deployments in a highly available and cost-effective manner.
Learning Objectives
This course teaches participants the following skills:
- Design for high availability, scalability, and maintainability.
- Integrate on-premises and cloud resources.
- Identify ways to optimize resources and minimize cost.
- Assess tradeoffs and make sound choices among Google Cloud Platform products.
- Implement processes that minimize downtime, such as monitoring and alarming, unit and integration testing, production resilience testing, and incident post-mortem analysis.
- Implement policies that minimize security risks, such as auditing, separation of duties and least privilege.
- Implement technologies and processes that assure business continuity in the event of a disaster.
Schedule
Certification Curriculum
The course includes presentations, demonstrations, and hands-on labs.
Defining the Service
Business-logic layer design
Data layer design
- Network edge configuration.
- Network integration with other environments, including on premises and multi-cloud.
- Network configuration for data transfer within the service, including load balancing and network location.
Network layer design
- Failure due to loss of resources.
- Scalable and resilient design.
- Strategies for coping with failure.
- Business continuity and disaster recovery, including restore strategy and data lifecycle management.
- Failure due to overload.
Design for resiliency, scalability, and disaster recovery
- Identity access and auditing.
- Google Cloud Platform security.
- Network access control and firewalls.
- Protections against denial of service.
- Resource sharing and isolation.
- Data encryption and key management.
Design for security
- Capacity planning.
- Pricing.
Capacity planning and cost optimization
- Monitoring and alerting.
- Deployment.
- Incident response.
Deployment, monitoring and alerting, and incident response
Prerequisites
While there are no specific prerequisites to achieving this certification beyond passing the Professional Cloud Architect Training exam, it is worth noting that experience with the required skills is key to a successful experience. Having passed the Associate Cloud Engineer exam and the G Suite exam and achieved the corresponding certifications, while not mandatory, will help you prepare for this level since they introduce a number of technologies covered in the Google Cloud Certified – Professional Cloud Architect Training Engineer exam.
Download Brochure
We offer Professional Cloud Architect Training in Singapore aimed at beginning Cloud Architect understanding that can lead to your Professional Cloud Architect certification. Download the brochure and check the different Focus Areas covered within these 3 days of training.
Certification Assessment
Prepare for the exam by following the Professional Cloud Architect learning path. Explore online training, in-person classes, hands-on labs, and other resources from Google Cloud.
Register and select the option to take the exam remotely or at a nearby testing centre.
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- Join Our Dynamic Community
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- Post-workshop support by the Coaches
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Training FAQ's
In the Machine Learning Training, you will learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models and offer high-performance predictions
The duration of Machine Learning Training is two-days.
Data Engineers and programmers interested in learning how to apply machine learning in practice or anyone interested in learning how to build and operationalize TensorFlow models can apply for Machine Learning Training.
With Machine Learning Training with TensorFlow Certification, you can strengthen your cloud knowledge, earn a digital certificate, and start preparing for an industry-recognized Google Cloud certification.
Participants should have experience coding in Python, knowledge of basic statistics, and knowledge of SQL and cloud computing.
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