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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: 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 3: Document Understanding | 30% | - Document Understanding Framework
|
| Topic 4: Communications Mining | 25% | - Taxonomy design and management - Analyze predictions and improve performance - Model training, annotation and refinement |
UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:
1. Having the taxonomy in a file, shared and updated across multiple projects, what is the most convenient way to load it in a UiPath Studio project?
A) Using DeserializeTaxonomy activity.
B) Using Load Taxonomy activity.
C) Using DocumentTaxonomy.Deserialize method inside an Assign activity.
D) Using Read Taxonomy activity.
2. How can a Pipeline be scheduled?
A) A Pipeline can be scheduled at a single future date.
B) A Pipeline can be scheduled at multiple future dates or with a recurring schedule.
C) A Pipeline can be scheduled at a single future date or with a recurring schedule.
D) A Pipeline can be scheduled with a recurring schedule.
3. Who is responsible for devising a strategy to prioritize processes during the Business Case and Technical Validation phase?
A) Project Manager
B) Solution Architect
C) Automation Developer
D) Business Analyst
4. What is a reason for pinning a UiPath Communications Mining Model?
A) To allow rollback of annotations to that model version.
B) To force the Ul to show predictions from that model version in explore
C) To allow AB comparing of the statistics of that model version with another one.
D) To delete all other model versions.
5. Why might labels have bias warnings in UiPath Communications Mining, even with 100% precision?
A) They have low recall.
B) They lack training examples.
C) They were trained using the "Shuffle" option extensively.
D) They were trained using the "Search" option extensively.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: B |






