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2025 UiPath UiPath-SAIAv1: UiPath Specialized AI Associate Exam (2023.10) Authoritative Study Tool

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q155-Q160):

NEW QUESTION # 155
Which of the following consumes Page Units?

A. Using ML Classifier on a 21-page document.
B. Using Intelligent Form Extractor on a 5-page document with 0 successful extractions.
C. Creation of a Document Validation Action in Action Center.
D. Applying OCR on a 10-page document.

Answer: D

Explanation:
According to the UiPath documentation, Page Units are the measure used to license Document Understanding products. Page Units are charged based on the number of pages processed by the Document Understanding models, such as extractors, OCR engines, and classifiers. Therefore, applying OCR on a 10-page document consumes Page Units, while the other options do not. The creation of a Document Validation Action in Action Center does not consume any Page Units, as it is a human-in-the-loop activity. Using ML Classifier on a 21- page document does not consume Page Units, as it is a free model. Using Intelligent Form Extractor on a 5- page document with 0 successful extractions does not consume Page Units, as the extractor only charges for successful extractions.
References:
AI Center - AI Units
Document Understanding - Metering & Charging Logic

NEW QUESTION # 156
Which of the following options contains the correct list of Default actions that can be found in Workflow Analyzer Settings?

A. Fatal, Error, Warning, Info, Trace
B. Error, Critical, Info, Warning, Verbose
C. Error, Info, Warning, Verbose
D. Exception, Info, Warning, Verbose

Answer: A

Explanation:
Reference: UiPath Workflow Analyzer

NEW QUESTION # 157
In UiPath Communications Mining, which phase is the starting point of the model training process, where similar intents and conversation themes are grouped?

A. Explore
B. Discover
C. Setup
D. Refine

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In UiPath Communications Mining, theDiscoverphase is the initial stage in which the system groups similar messages or conversations based on content. These clusters help users identify patterns and common intents, which serve as a foundation for defininglabels and training taxonomy.
* This unsupervised learning approach is essential forbootstrapping model trainingwith minimal manual intervention.
* UiPath Documentation Reference:Discover Phase - Communications Mining

NEW QUESTION # 158
What does the Export stage of the Document Understanding Framework do?

A. Classifies the document as one of the predefined document types.
B. Allows a human to validate and correct the extracted data.
C. Extracts the text out of the image document using OCR (Optical Character Recognition).
D. Converts the result of extraction to a dataset or to a customized format.

Answer: D

Explanation:
According to the UiPath documentation portal1, the Export stage of the Document Understanding Framework is the final stage of the document processing workflow, where the extracted data is converted to a dataset or to a customized format, such as Excel, JSON, or XML. The Export stage enables you to easily export data for training ML models, using the Export files dialog box in Data Manager or Document Manager. The Export stage also allows you to export the schema of the fields and their configurations, which can be imported into a different session. The Export stage supports different export options, such as current search results, all labeled, schema, or all. The Export stage also provides validation rules, such as requiring at least 10 labeled documents or pages for each field, and at least one document for each classification option1. Therefore, option A is the correct answer, as it describes the main function and benefit of the Export stage. Option B is incorrect, as it refers to the Data Validation stage, which is the previous stage of the document processing workflow, where a human can review and correct the extracted data using the Validation Station or the Present Validation Station activities2. Option C is incorrect, as it refers to the Classification stage, which is the second stage of the document processing workflow, where the document is classified as one of the predefined document types using the Classify Document Scope activity and a classifier of choice3. Option D is incorrect, as it refers to the Digitization stage, which is the first stage of the document processing workflow, where the text is extracted out of the image document using OCR (Optical Character Recognition) using the Digitize Document activity and an OCR engine of choice.
References: 1 Document Understanding - Export Documents 2 Document Understanding - Data Validation 3 Document Understanding - Classification Document Understanding - Digitization

NEW QUESTION # 159
Which of the following is a best practice when choosing a UiPath ML (Machine Learning) Extractor?

A. The cost of the ML Extractor should be the main consideration when choosing an ML Extractor.Select the ML Extractor that offers the lowest price, regardless of its performance or suitability for the specific document understanding needs.
B. The popularity of the ML Extractor among other UiPath users should be the primary factor when choosing a UiPath ML Extractor.Opt for the ML Extractor that has the highest number of downloads or positive reviews.
C. The size of the ML Extractor is the most important factor to consider when choosing an ML Extractor.Bigger models always perform better and provide more accurate extraction results because the development team invested time and effort into creating the algorithm, which in turn will result in better performance for the trained model.
D. Consider the document types, language, and data quality when choosing an ML Extractor.It is important to select one that is specifically trained or optimized for the document types being processed.
It is also important to take into account the quality and diversity of the training data used to train the ML Extractor to ensure accurate and reliable extraction results.

Answer: D

Explanation:
The ML Extractor is a data extraction tool that uses machine learning models provided by UiPath to identify and extract data from documents. The ML Extractor can work with predefined document types, such as invoices, receipts, purchase orders, and utility bills, or with custom document types that are trained using the Data Manager and the Machine Learning Classifier Trainer12.
According to the best practice, the ML Extractor should be chosen based on the document types, language, and data quality of the documents being processed. It is important to select an ML Extractor that is specifically trained or optimized for the document types that are relevant for the use case, as different document types may have different layouts, fields, and formats. It is also important to take into account the language of the documents, as some ML Extractors may support only certain languages or require specific language settings. Moreover, it is important to consider the quality and diversity of the training data used to train the ML Extractor, as this may affect the accuracy and reliability of the extraction results. The training data should be representative of the real-world data, and should cover various scenarios, variations, and exceptions3.
References: 1: Machine Learning Extractor - UiPath Activities 2: Machine Learning Classifier Trainer - UiPath Document Understanding 3: Data Extraction - UiPath Document Understanding

NEW QUESTION # 160
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