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New Released UiPath UiPath-SAIAv1 Questions Verified by Experts [2025]

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q229-Q234):

NEW QUESTION # 229
What are the two main data extraction methodologies used in document understanding processes?

A. Manual and model-based data extraction.
B. Hybrid and manual data extraction.
C. Rule-based and hybrid data extraction.
D. Rule-based and model-based data extraction.

Answer: D

Explanation:
According to the UiPath documentation, there are two common types of data extraction methodologies used in document understanding processes: rule-based data extraction and model-based data extraction12. Rule- based data extraction targets structured documents, such as forms, invoices, or receipts, that have a fixed layout and a predefined set of fields. Rule-based data extraction uses predefined rules, such as regular expressions, keywords, or coordinates, to locate and extract the relevant data from the documents1. Model- based data extraction is used to process semi-structured and unstructured documents, such as contracts, emails, or reports, that have a variable layout and a diverse set of fields. Model-based data extraction uses machine learning models, such as neural networks, to learn from examples and extract the relevant data from the documents1. Both methodologies have their advantages and limitations, and depending on the use case, they can be used separately or in combination, in a hybrid approach2.
References: 1: Data Extraction Overview 2: Document Processing with Improved Data Extraction

NEW QUESTION # 230
Which UiPath Communications Mining model performance factor relates to the proportion of messages in the dataset that have informative label predictions?

A. Balance.
B. Average label performance.
C. Coverage.
D. Underperforming labels.

Answer: C

Explanation:
In UiPath Communications Mining, the term Coverage refers to the proportion of messages in the dataset that have informative label predictions. This is an important metric that indicates how much of the dataset the model is able to classify with meaningful and relevant labels. High coverage means that the model is effectively assigning labels to a large portion of the data, which is crucial for ensuring the model's usefulness in automating communication mining tasks.
For more details, refer to:
UiPath Communications Mining Performance Factors: Model Coverage and Accuracy Communications Mining: Coverage and Other Metrics

NEW QUESTION # 231
Which statement accurately describes out-of-the-box models in UiPath?

A. Out-of-the-box models are custom-built models created specifically for each project.
B. Out-of-the-box models are pre-trained models that cover a wide range of document types.
C. Out-of-the-box models require extensive training and customization before they can be used effectively.
D. Out-of-the-box models are only available for specific languages and cannot be adapted for multilingual documents.

Answer: B

Explanation:
UiPath provides out-of-the-box pre-trained models that are ready for use and cover a wide variety of document types. These models can be used as-is for common use cases or fine-tuned based on specific requirements, making them versatile for different projects

NEW QUESTION # 232
Which UiPath product is most suitable for processing invoices?

A. UiPath Process Mining.
B. UiPath Task Mining.
C. UiPath Document Understanding.
D. UiPath Communications Mining.

Answer: C

Explanation:
UiPath Document Understanding is the most suitable product for processing invoices. It provides tools for digitization, classification, data extraction, and validation, which are ideal for structured and semi-structured documents like invoices.
Reference: UiPath Document Understanding for Invoices

NEW QUESTION # 233
What is the default visibility of an ML skill?

A. An ML skill is by default public and can't be made private.
B. An ML skill is by default public and can be made private.
C. An ML skill is by default private and can't be made public.
D. An ML skill is by default private and can be made public.

Answer: D

Explanation:
An ML skill is a consumer-ready, live deployment of an ML or OS package that can be used in RPA workflows. By default, an ML skill is private, which means it can only be accessed by the users who have the permission to view and manage the project that contains the skill. However, an ML skill can be made public by enabling the Public Skill option in the ML Skill Details page. This will generate a public URL and an API key for the skill, which can be used to access the skill from any external system or application12.
References: 1: AI Center - About ML Skills 2: Make ML Skills and Datasets public via URL + API Key - Preview

NEW QUESTION # 234
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John Young John Young

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