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UiPath UiPath-SAIv1 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Center & ML Integration | 25% | - Model lifecycle management - Integrate AI models with Studio workflows - Deploy and monitor ML models |
| Topic 2: Document Understanding | 30% | - Document Understanding Framework
|
| Topic 3: AI-Powered Automation Design | 20% | - Select appropriate AI capabilities for business problems - Design scalable and reliable AI-enabled automation solutions - Apply AI governance and security principles |
| Topic 4: Communications Mining | 25% | - Analyze predictions and improve performance - Model training, annotation and refinement - Taxonomy design and management |
UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:
Question 1
Which is the correct description of the Configure Extractors Wizard?
A. A mandatory step in the extractor configuration that allows choosing which extractors are applied to each field.
B. An optional step in the extractor configuration which allows choosing which extractors are applied to each document type.
C. A mandatory step in the extractor configuration that allows choosing which extractors are applied to each document type.
D. A mandatory step in the extractor configuration that allows choosing which extractors are applied to each document type and field.
Question 2
As a best practice, who should perform the data labeling?
A. Business Analysts.
B. Automation RPA Developers.
C. Subject Matter Experts.
D. Data Scientists.
Question 3
Which statement accurately describes out-of-the-box models in UiPath?
A. Out-of-the-box models are pre-trained models that cover a wide range of document types.
B. Out-of-the-box models are only available for specific languages and cannot be adapted for multilingual documents.
C. Out-of-the-box models require extensive training and customization before they can be used effectively.
D. Out-of-the-box models are custom-built models created specifically for each project.
Question 4
What happens when multiple users try to label the same document concurrently?
A. The changes made by one user override the changes made by others.
B. Concurrent labeling is not allowed.
C. The changes made by all users are saved successfully.
D. A warning message is displayed to the other user(s) indicating unsuccessful changes.
Question 5
What is supervised learning?
A. 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.
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 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.
D. 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).
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: A | Question 4 Answer: B | Question 5 Answer: C |







