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How to book the CAU305 Exam

These are following steps for registering the CyberArk CAU305 exam.

• Step 1: Visit to Pearson VUE Exam Registration
• Step 2: Signup/Login to Pearson VUE account
• Step 3: Search for CyberArk CAU305 Exam Certifications Exam
• Step 4: Select Date, time and confirm with payment method

What is the duration of the CAU305 Exam

• Passing Score: 70%
• Number of Questions: 40
• Format: Multiple choices, multiple answers
• Length of Examination: 90 minutes

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CAU305 Exam topics

Candidates must know the Defender + Sentry exam topics before they start of preparation because it will really help them in hitting the core. Our CAU-305 practice test and CAU-305 practice exams will include the following topics. These are covered in our CAU-305 exam dumps.

• Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?

• Defining the CyberArk Privileged Account Security Solution Architecture

• What workflow changes can be done through the board by board administrators?

• What types of workflow changes can Project Administrators make if Extended Project Administration is activated?

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

• What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?

• Distributed vs. single machine

• Verification and monitoring

• Building and running test suites

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

• Use of edge compute

• Operationalizing machine learning models

• What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?

• Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?

• Data security (encryption, key management)

• Continuous evaluation

• ML APIs (e.g., Vision API, Speech API)

• Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)

• Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))

• Ingesting appropriate data

• Who can change a Project Key, and what are the effects on issues in the project?

• What is an Issue Collector and what permissions are needed to configure it?

• Data staging, cataloging, and discovery

• Designing for security and compliance

• Which project details can be added and changed by Project Administrators?

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

• Where are all the places you need to look to fully identify what permissions a particular user has?

• What are the configuration options for all the out-of-box reports and gadgets (except Agile reports and gadgets)? What is their behavior and expected results?

• Ensuring privacy (e.g., Data Loss Prevention API)

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

• When is it best to use components, and when is it best to use a custom field instead?

• Which export options are available from the Issue Navigation? The following will be discussed here:

• How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)

• What is the importance of the Browse Projects permission?

• Leveraging pre-built ML models as a service

• Impact of dependencies of machine learning models

• Securely Managing the System Architecture

• What things may need to be updated as a result of workflow changes of any kind?

• Monitoring Privileged Account Access

• What are the use cases where it is best to use Project Roles rather than Groups?

• Choosing between ACID, idempotent, eventually consistent requirements

• Resizing and autoscaling resources

• Choosing the appropriate training and serving infrastructure

• What are the uses of Project Category in Jira?

• Measuring, monitoring, and troubleshooting machine learning models

• Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?

• Identity and access management (e.g.,Cloud IAM)

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

• Conversational experiences (e.g., Dialogflow)

• What is the relationship between screens, screen schemes and issue type screen schemes?

• Ensuring reliability and fidelity

• Mapping to current and future business requirements

• How do combinations of permissions work together to enable specific actions?

• Assessing, troubleshooting, and improving data representations and data processing infrastructure

• Pipeline monitoring (e.g., Stackdriver)

• What changes can be performed on statuses and transitions?

• Ensuring scalability and efficiency

• Designing for data and application portability (e.g., multi-cloud, data residency requirements)

• Deploying an ML pipeline

• Target Hosts Using Privileged Session Manager

• What are all the various factors that influence whether a field is visible on a screen?

• Performing data preparation and quality control (e.g., Cloud Dataprep)

• Ensuring flexibility and portability

The benefit in Obtaining the CAU305 Exam Certification

The recertification exam provides the practical knowledge and technical skills to securely design, install, and configure the CyberArk Privileged Access Security Solution. The candidates will gain valuable hands-on experience installing CyberArk components, configuring Authentication Types, and System Integrations (SIEM, SMTP, SNMP), using our step-by-step exercise guide, official product documentation and a dedicated lab environment.

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