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Updated: Sep 06, 2026
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| Certification Vendor: | UiPath |
|---|---|
| Exam Name: | UiPath Certified Professional Specialized AI Professional v1.0 |
| Exam Number: | UiPath-SAIv1 |
| Certificate Validity Period: | 3 years |
| Exam Price: | USD 300 |
| Exam Duration: | 120 minutes |
| Passing Score: | 70% |
| Exam Format: | Multiple choice, Scenario-based, Multiple response |
| Available Languages: | English |
| Related Certifications: | UiPath Certified Professional UiPath Certified Specialized AI Associate |
| Real Exam Qty: | 45 - 60 |
| Recommended Training: | UiPath Academy - Specialized AI Professional Learning Plan |
| Exam Registration: | Pearson VUE Registration |
| Sample Questions: | UiPath UiPath-SAIv1 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No mandatory prerequisites; recommended experience with UiPath platform and AI concepts |
| Official Syllabus URL: | https://www.uipath.com/learning/certification/specialized-ai-professional |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Communications Mining | 25% | - Analyze predictions and improve performance - Taxonomy design and management - Model training, annotation and refinement |
| Topic 2: AI Center & ML Integration | 25% | - Model lifecycle management - Integrate AI models with Studio workflows - Deploy and monitor ML models |
| Topic 3: AI-Powered Automation Design | 20% | - Apply AI governance and security principles - Design scalable and reliable AI-enabled automation solutions - Select appropriate AI capabilities for business problems |
| Topic 4: Document Understanding | 30% | - Document Understanding Framework
|
Question 1
How are UiPath RPA and AI Center used for process improvement?
A. UiPath RPA and AI Center work together in process improvement by leveraging RPA capabilities to automate repetitive tasks and integrating AI Center to enhance decision-making and cognitive abilities.RPA bots can collect data, perform actions, and feed information to ML models in AI Center, which in turn can analyze the data and make predictions.
B. UiPath RPA and AI Center work together in process improvement by utilizing RPA bots to execute models deployed in Action Center that can be monitored in Insights. The ML models process data and generate insights, which are then used by the RPA bots to make informed decisions and carry out automated actions.
C. UiPath RPA and AI Center have overlapping functionalities, so they are not designed to work together in process improvement. Each tool serves different purposes and is used independently to achieve automation and AI capabilities, respectively.
D. UiPath RPA and AI Center are independent tools that do not work together in process improvement.
RPA focuses on task automation, while AI Center is primarily used for training and deploying machine learning models.
Question 2
Why is having high coverage important for an automation-focused use case in UiPath Communications Mining?
A. High coverage on the model means that fewer communications will be sent for manual review and that fewer automatable processes are missed.
B. With high coverage, you can increase the amount of data provided downstream via Streams.
C. The higher the coverage, the lower the model's recall, resulting in greater throughput of automatable processes.
D. High coverage ensures that the software consumes less computational resources, resulting in cost savings for the organization implementing the automation.
Question 3
Why might labels have bias warnings in UiPath Communications Mining, even with 100% precision?
A. They were trained using the "Search" option extensively.
B. They were trained using the "Shuffle" option extensively.
C. They lack training examples.
D. They have low recall.
Question 4
Which technology enables UiPath Communications Mining to analyze and enable action on messages?
A. Robotic Process Automation
B. Cloud Computing.
C. Natural Language Processing (NLP)
D. Virtual Reality.
Question 5
Considering the Process Design phase, what should be Taken into consideration as a best practice when creating the scope for the automation?
A. Document Types. Technical Criteria, Templates. Languages, Scans/Digital docs, OCR quality.
B. Document Types. Taxonomy. Templates. Languages. Scans/Digital docs, Success Criteria. Technical Criteria.
C. Document Types. Templates. Technical Criteria. Languages. Scans/Digital docs. Success Criteria. OCR engines.
D. Document Types. Taxonomy. Languages. Success Criteria. OCR, ML Model.
Solutions:
| Question 1 Answer: A | Question 2 Answer: A | Question 3 Answer: C | Question 4 Answer: C | Question 5 Answer: B |
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