Learn with UiPath : UiPath-SAIv1 training material for 100% pass
Updated: Jul 11, 2026
No. of Questions: 213 Questions & Answers with Testing Engine
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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:
1. What is the primary purpose of assigning labels to messages within a dataset in UiPath Communications Mining?
A) To apply labels to a maximum amount of data to enhance model performance.
B) To formulate a comprehensive training set that closely reflects the entirety of the dataset.
C) To provide the platform with a collection of keywords associated with each label for predicting other instances.
D) To allocate 20 training examples for each label.
2. For what type of documents is it recommended to use the Form Extractor?
A) For structured or semi-structured documents in which layouts of different document providers vary greatly.
B) For use cases in which non-variable format documents need to be processed.
C) For structured or semi-structured documents where for certain fields, data is always found in a strict, predictable format and context.
D) For structured or semi-structured documents where the extraction method is based on a set of FlexiCapture definition files.
3. Having the following list of documents:
Invoice1.pdf, Invoice2.raw, Invoice3.gif, Invoice4.jpg, Invoice5.docx
Please choose all the files that can be used in the DocumentPath property of the Classify Document Scope activity.
A) Invoice1.pdf, Invoice2.raw, Invoice3.gif, Invoice4.jpg
B) Invoice1.pdf, Invoice3.gif, Invoice5.docx
C) Invoice1.pdf, Invoice4.jpg, Invoice5.docx
D) Invoice1.pdf, Invoice3.gif, Invoice4.jpg
4. What is supervised learning?
A) Supervised learning is a machine learning paradigm in which algorithms try to solve a problem only by trial and error and using a system of rewards and punishments.
There is no need for labeled input/output pairs to be presented. Instead, the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge).
B) Supervised learning is a machine learning paradigm that refers to algorithms that learn patterns from unlabeled data.There are only input variables, but no corresponding output variables. The goal of the algorithm is to model the underlying structure of the data, but there are no correct answers and no teachers.
C) Supervised learning is a machine learning paradigm in which algorithms try to solve a problem in an uncertain, potentially complex environment only by trial and error and using a system of rewards and punishments.
There are no correct answers, but feedback is given in the form of rewards and penalties.
D) Supervised learning is a machine learning paradigm with the goal of learning a function that maps input variables with output variables.
In every case there is a correct answer, so the aim is to train the model until it reaches an acceptable level of performance in predicting the outcome, at which point the learning stops.
5. Which OCR (Optical Character Recognition) option is recommended to be initially utilized for document processing in a project?
A) UiPath CJK (for Chinese. Japanese. Korean).
B) OmniPage.
C) UiPath Document OCR.
D) Tesseract OCR.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: C |
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