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Certification Path

CAU-401 is an advanced course and requires EPM certification as a pre-requisite.

Reference: https://training.cyberark.com/instructor-led-training/cyberark-end-point-manager

Who should take the CAU-401 exam

CAU-401 is for customers who administer EPM and partners who implement the EPM Solution. The CyberArk CDE certification is valid for 18 months so it can be for people who want to improve their long term career goals.

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CAU-401 Exam topics

Candidates must know the EPM topics before they start of preparation because it will really help them solving the problems. Our CAU-401 practice test and CAU-305 practice exams will include the following topics. These are covered in our CAU-305 exam dumps.

• Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
• 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 is an Issue Collector and what permissions are needed to configure it?
• Which export options are available from the Issue Navigation?
• Deploy and upgrade the EPM Agent
• Designing for data and application portability (e.g., multi-cloud, data residency requirements)
• Monitoring Privileged Account Access
• Data staging, cataloging, and discovery
• Choosing between ACID, idempotent, eventually consistent requirements
• Conversational experiences (e.g., Dialogflow)
• ML APIs (e.g., Vision API, Speech API)
• Ensuring reliability and fidelity
• Pipeline monitoring (e.g., Stackdriver)
• Defining the CyberArk Privileged Account Security Solution Architecture
• Data security (encryption, key management)
• Which project details can be added and changed by Project Administrators?
• Impact of dependencies of machine learning models
• Securely Managing the System Architecture
• Target Hosts Using Privileged Session Manager
• Performing data preparation and quality control (e.g., Cloud Dataprep)
• Retrieve logs and perform simple troubleshooting tasks
• What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?
• Choosing the appropriate training and serving infrastructure
• Common sources of error (e.g., assumptions about data)
• Hardware accelerators (e.g., GPU, TPU)
• What is the importance of the Browse Projects permission?
• Operationalizing machine learning models
• What changes can be performed on statuses and transitions?
• Describe the EPM solution and architecture
• Configure ransomware and threat protection
• Ensuring flexibility and portability
• What is the relationship between screens, screen schemes and issue type screen schemes?
• Who can change a Project Key, and what are the effects on issues in the project?
• Ensuring scalability and efficiency
• Mapping to current and future business requirements
• Verification and monitoring
• Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
• Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
• Distributed vs. single machine
• What are all the various factors that influence whether a field is visible on a screen?
• What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?
• What things may need to be updated as a result of workflow changes of any kind?
• How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)
• Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))
• How do combinations of permissions work together to enable specific actions?
• Leveraging pre-built ML models as a service
• Identity and access management (e.g.,Cloud IAM)
• Describe implementation and roll-out best practices
• What are the uses of Project Category in Jira?
• Deploying an ML pipeline
• Assessing, troubleshooting, and improving data representations and data processing infrastructure
• Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?
• Where are all the places you need to look to fully identify what permissions a particular user has?
• Resizing and autoscaling resources
• 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?
• Continuous evaluation
• Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?
• Building and running test suites
• Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?
• What are the use cases where it is best to use Project Roles rather than Groups?
• Ingesting appropriate data
• Ensuring privacy (e.g., Data Loss Prevention API)
• Designing for security and compliance
• When is it best to use components, and when is it best to use a custom field instead?
• Measuring, monitoring, and troubleshooting machine learning models
• What workflow changes can be done through the board by board administrators?
• Use of edge compute