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UiPath UiPath-SAIv1 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| AI-Powered Automation Design | 20% | - Apply AI governance and security principles - Select appropriate AI capabilities for business problems - Design scalable and reliable AI-enabled automation solutions |
| AI Center & ML Integration | 25% | - Deploy and monitor ML models - Integrate AI models with Studio workflows - Model lifecycle management |
| Communications Mining | 25% | - Model training, annotation and refinement - Analyze predictions and improve performance - Taxonomy design and management |
| Document Understanding | 30% | - Document Understanding Framework
|
UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:
1. What is the primary advantage of the One Click Extraction feature in UiPath's Document Understanding interface?
A) It allows training document extractors without manually creating Datasets, Pipelines, and ML Skills in AI Center.
B) It allows training document extractors without manually creating Datasets and Pipelines, but you need to manually deploy the ML Skills in AI Center.
C) It provides a simplified way to manually create Datasets, Pipelines, and Datasets for document extraction.
D) It automates the creation of document extractors by automatically creating Datasets, Pipelines, and ML Skills but requires manual creation of Pipelines.
2. What does a UiPath Communications Mining taxonomy include?
A) Labels and sources.
B) General fields and datasets.
C) Labels and general fields.
D) Messages, labels, and general fields.
3. What does Data Extraction do?
A) Identifies words and their coordinates from images and PDFs.
B) Identifies and extracts specific information that should be processed.
C) Applies rules for validating that the information extracted from a document is correct.
D) Digitizes the document that should be processed.
4. What fields are available when creating an Al Center project?
A) Name, description, and permissions.
B) Name and description.
C) Name and labels.
D) Name, description, and labels.
5. What can the Custom Named Entity Recognition out-of-the-box model be used for?
A) Extract and classify text in emails, letters, web pages, research papers, and call transcripts.
B) Relate customer questions to FAQ documents and automatically pull responses from these documents.
C) Understand sentiment in product reviews, customer surveys, social media posts, and emails.
D) Classify text in resumes, emails, web pages, and other formats.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: A |


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