UiPath-SAIAv1 UiPath Specialized AI Associate Practice Questions
Prepare for UiPath-SAIAv1 with more than an answer.
- Exam fee
- $150 USD
- Level
- Associate
- Valid for
- 3 years
Domains covered on the exam 5
- UiPath Document Understanding Fundamentals25%
- UiPath Communications Mining Fundamentals25%
- UiPath AI Center Fundamentals15%
- UiPath Platform and Automation Development20%
- Autopilot and AI-Assisted Development15%
- 1
A Communications Mining model shows high Precision but low Recall for the label 'Urgent'. What does this indicate about the model's performance?
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Correct answer: B
Precision = Quality of positive predictions (few false positives). Recall = Quantity of positive predictions found (few false negatives). High Precision/Low Recall means it's conservative: rarely wrong when it guesses, but misses a lot.
- 2
Which file format is primarily used to upload a new dataset into UiPath Communications Mining?
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Correct answer: C
CSV is the standard format for uploading tabular data (like email exports with columns for Subject, Body, Date) into Communications Mining.
- 3
In the 'Explore' phase of Communications Mining, what is the purpose of the 'Shuffle' function?
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Correct answer: B
Shuffle ensures the user sees a representative sample of the data, rather than just the easiest or most clustered examples, which prevents the model from overfitting to specific patterns found in clusters.
- 4
A business analyst is reviewing the 'Label Summary' in Communications Mining. They notice a label 'Pricing Inquiry' has a very high volume but a very low 'Automation Potential' score. What does this combination typically suggest?
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Correct answer: C
High volume means it happens often, but low automation potential suggests the content is varied, complex, or lacks structured data needed for RPA.
- 5
A telecom company uses Communications Mining to analyze customer emails. They need to extract the 'Account Number' (a 9-digit number) and the 'Service Address'. The Account Number format is strict, but the Address is free-text. Which field configuration strategy is best?
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Correct answer: D
Regex is perfect for fixed patterns like 9-digit IDs. ML spans are designed for variable text like addresses that depend on context.
- 6
A developer is configuring the Taxonomy for a Document Understanding project intended to process both Invoices and Purchase Orders. The project requires that the 'Vendor Name' field be extracted from both document types, but the 'Payment Terms' field is only relevant for Invoices. Using the Taxonomy Manager in UiPath Studio, how should the developer structure this taxonomy to ensure efficient extraction and validation?
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Correct answer: B
The Taxonomy Manager allows for a hierarchical structure (Group > Category > Document Type). Fields are defined at the Document Type level. Since 'Vendor Name' is needed for both but 'Payment Terms' only for one, defining them as distinct Document Types within the same Category allows for specific field definitions per type while maintaining logical grouping.
- 7
During the 'Digitization' step of a Document Understanding workflow, a developer encounters a set of PDF documents that contain both native text and scanned images. The goal is to extract text from the entire document while ensuring the highest possible accuracy for the scanned portions. Which configuration of the 'Digitize Document' activity is optimal for this scenario?
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Correct answer: C
The 'Auto' setting determines if the PDF has embedded text. If yes, it extracts it directly; if no (or for images within), it applies OCR. UiPath Document OCR is optimized for document processing workflows.
- 8
A developer is implementing the 'Classification' stage in a Document Understanding process. The project deals with three distinct document types: Passports, ID Cards, and Driver Licenses. Which classifier is most appropriate to use if the developer wants to leverage the visual layout and structure of these documents for identification without training a custom model?
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Correct answer: A
The Intelligent Keyword Classifier classifies documents based on word vectors found within the document. It is effective for distinct document types and allows for learning from a small set of examples during configuration without full ML model training.
- 9
In a Document Understanding project, a specific field 'Invoice Number' typically follows the text 'Inv No:' or 'Invoice #'. However, in 5% of cases, it appears in a table without a label. Which extraction strategy provides the most robust solution for this field?
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Correct answer: B
A hybrid approach leverages the determinism of rules (Regex) for standard cases and the generalization of AI (ML Extractor) for complex, unlabeled cases. Prioritizing Regex ensures speed and accuracy for the 95% standard cases.
- 10
A developer notices that data validated by a human user in the 'Present Validation Station' is not reflecting in the final output DataTable. The workflow includes 'Present Validation Station' followed immediately by 'Export Extraction Results'. What is the most likely cause of this issue?
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Correct answer: C
The 'Present Validation Station' activity outputs a NEW extraction results object containing the human corrections. If the subsequent Export activity uses the original extraction results, the corrections are ignored.
