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UiPath UiPath-SAIv1 Exam Syllabus Topics:
| Section | Weight | Objectives |
| UiPath Document Understanding | 40% | - ML Models
- 1. Configure classification and extraction
- 2. Out-of-the-box models
- 3. Train and deploy ML models
- Document Understanding Framework
- 1. Data extraction and validation
- 2. Configure Document Understanding activities
- 3. Taxonomy definition and management
|
| Solution Design and Best Practices | 10% | - Implementation Best Practices
- 1. Deployment strategies
- 2. Maintenance and monitoring
- 3. Testing and validation
- Architecture Design
- 1. End-to-end solution design
- 2. Scalability and performance
- 3. Error handling and exception management
|
| UiPath AI Center | 20% | - Integration
- 1. Connect with UiPath Studio
- 2. Pipeline management
- 3. Data management
- ML Model Management
- 1. Retrain and versioning
- 2. Monitor model performance
- 3. Deploy and manage ML models
|
| UiPath Communications Mining | 30% | - Actionable Insights
- 1. Dashboard and reporting
- 2. Prioritization and routing
- 3. Trend analysis
- Communications Mining Fundamentals
- 1. Define taxonomy and labels
- 2. Configure data sources
- 3. Train and evaluate models
|
UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:
1. A project contains a Try Catch activity in the "Main.xaml" workflow. In the Catches block, there is a Rethrow activity. The process is started from Orchestrator and an exception is caught in the Try section. What is the expected result?
A) Job is completed with a "Faulted" state.
B) Exception Pop-up is displayed on the robot machine.
C) Job is completed with a "Stopped" state.
D) Job is completed with a "Successful" state.
2. What is the relationship between AI Center and UiPath Document Understanding?
A) AI Center is the infrastructure on top of which UiPath Document Understanding machine learning models run.
B) AI Center is the infrastructure on top of which UiPath Document Understanding digitization runs.
C) Document Understanding is the infrastructure on which AI Center machine learning models run.
D) Document Understanding is the infrastructure on which AI Center digitization runs.
3. In UiPath Communications Mining, what does the Reports section contain?
A) Tools for evaluating model performance.
B) Tools for comparing different model versions.
C) Tools for message analytics and monitoring.
D) Tools for evaluating label and entity performance.
4. What information should be provided when adding a classification label for the OOB (Out Of the Box) labeling template?
A) Name, Input to be labeled. Attribute name, and Shortcut.
B) Name, Classification Type. Attribute name. Color, and Shortcut.
C) Name, Classification type, Attribute name, and Shortcut.
D) Name, Classification type. Input to be labeled. Attribute name. Shortcut, and Color.
5. What is the Machine Learning Extractor?
A) A tool using machine learning models to identify and report on data targeted for data extraction.
B) A tool that helps extract data from different document structures, and is particularly useful when the same document has multiple formats.
C) An extraction model that can be enabled and trained in Al Center. For better accuracy. 25 documents per model are recommended to train the model.
D) A specialized model that can recognize multiple languages in the same document using API calls to a Hugging Face model with over 250 languages.
Solutions:
Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: B |