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What is the duration of the CAU305 Exam
- Number of Questions: 40
- Format: Multiple choices, multiple answers
- Length of Examination: 90 minutes
- Passing Score: 70%
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CAU305 Exam topics
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Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
Which business requirements necessitate the use of separate issue types in a project (e.g. different screens, workflows, etc.)?
What is an Issue Collector and what permissions are needed to configure it?
What are the features, uses, limitations/restrictions of workflow changes, especially the Simplified Workflow?
Deploying an ML pipeline
Pipeline monitoring (e.g., Stackdriver)
What features are available for Jira Software projects, and to users who have Jira Software application access (as compared to just Jira Core)?
Conversational experiences (e.g., Dialogflow)
What are all the various factors that influence whether a field is visible on a screen?
Ingesting appropriate data
Ensuring flexibility and portability
What things may need to be updated as a result of workflow changes of any kind?
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?
Hardware accelerators (e.g., GPU, TPU)
What workflow changes can be done through the board by board administrators?
Resizing and autoscaling resources
Data security (encryption, key management)
Who can change the Simplified Workflow? What are the limitations on changes to the Simplified Workflow?
Common sources of error (e.g., assumptions about data)
Mapping to current and future business requirements
What is the relationship between screens, screen schemes and issue type screen schemes?
Continuous evaluation
ML APIs (e.g., Vision API, Speech API)
Target Hosts Using Privileged Session Manager
Assessing, troubleshooting, and improving data representations and data processing infrastructure
What are the use cases where it is best to use Project Roles rather than Groups?
Ensuring scalability and efficiency
Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
Where are all the places you need to look to fully identify what permissions a particular user has?
Performing data preparation and quality control (e.g., Cloud Dataprep)
Identity and access management (e.g.,Cloud IAM)
Distributed vs. single machine
What is the importance of the Browse Projects permission?
What changes can be performed on statuses and transitions?
Ensuring reliability and fidelity
How do combinations of permissions work together to enable specific actions?
Choosing the appropriate training and serving infrastructure
Who can change a Project Key, and what are the effects on issues in the project?
Choosing between ACID, idempotent, eventually consistent requirements
Defining the CyberArk Privileged Account Security Solution Architecture
What are the uses of Project Category in Jira?
Building and running test suites
Which export options are available from the Issue Navigation? The following will be discussed here:
Verification and monitoring
Operationalizing machine learning models
Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
Ensuring privacy (e.g., Data Loss Prevention API)
Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))
Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
Use of edge compute
Which configurations (schemes, versions, components, etc) are shared versus unique when new projects are (1) created from template or (2) with a shared configuration?
What types of workflow changes can Project Administrators make if Extended Project Administration is activated?
Impact of dependencies of machine learning models
Designing for data and application portability (e.g., multi-cloud, data residency requirements)
How are valid JQL queries written? What operators and arguments are valid for various JQL functions (e.g. membersOf(), StartOfDay(), WAS, CHANGED, etc.)
Which project details can be added and changed by Project Administrators?
Securely Managing the System Architecture
Designing for security and compliance
Monitoring Privileged Account Access
Data staging, cataloging, and discovery
Measuring, monitoring, and troubleshooting machine learning models
Leveraging pre-built ML models as a service
When is it best to use components, and when is it best to use a custom field instead?
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