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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.

• Conversational experiences (e.g., Dialogflow)

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

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

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

• Deploying an ML pipeline

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

• Monitoring Privileged Account Access

• Distributed vs. single machine

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

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

• Ensuring reliability and fidelity

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

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

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

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

• Verification and monitoring

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

• Ensuring flexibility and portability

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

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

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

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

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

• Continuous evaluation

• What are the uses of Project Category in Jira?

• Use of edge compute

• Building and running test suites

• Mapping to current and future business requirements

• Leveraging pre-built ML models as a service

• Target Hosts Using Privileged Session Manager

• Ingesting appropriate data

• Pipeline monitoring (e.g., Stackdriver)

• Ensuring scalability and efficiency

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

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

• What changes can be performed on statuses and transitions?

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

• Data staging, cataloging, and discovery

• Defining the CyberArk Privileged Account Security Solution Architecture

• What is the importance of the Browse Projects permission?

• Measuring, monitoring, and troubleshooting machine learning models

• Securely Managing the System Architecture

• Operationalizing machine learning models

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

• Choosing the appropriate training and serving infrastructure

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

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

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

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

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

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

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

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

• Choosing between ACID, idempotent, eventually consistent requirements

• Impact of dependencies of machine learning models

• Designing for security and compliance

• 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?

• Data security (encryption, key management)

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

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

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

• Resizing and autoscaling resources

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

How to study the CAU305 Exam

Recertifications are an important part of maintaining credentials and status of the candidate. Practice exams and knowledge exam dumps are built to make students comfortable with the real exam environment. Exam-Killer expert team recommends you to prepare notes on these topics as you go along preparing with it and don't forget to practice CAU-305 practice exams and revise CAU-305 exam dumps.

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