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Free UiPath UiPath-SAIAv1 Dumps - UiPath-SAIAv1 Practice Test Engine

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Free UiPath UiPath-SAIAv1 Dumps - UiPath-SAIAv1 Practice Test Engine

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UiPath UiPath-SAIAv1 Exam Syllabus Topics:
TopicDetails
Topic 1
  • Workflow Analyzer: This section of the exam measures skills of RPA developers and covers using Workflow Analyzer and validation tools to identify errors, maintain project compliance, and ensure workflow efficiency during development.
Topic 2
  • Integration Service: This section of the exam measures skills of automation analysts and covers the use of UiPath Integration Service, its connectors, and triggers, showing how these elements enable smooth interaction between UiPath and third-party systems.
Topic 3
  • UiPath Communications Mining: This section of the exam measures skills of RPA developers and covers the application of Communications Mining in automation and analytics. It distinguishes this capability from Task Mining and Process Mining, explains the interface, and describes use cases.
Topic 4
  • Orchestrator: This section of the exam measures skills of RPA developers and covers Orchestrator's structure and functionality, including entities at the tenant and folder level. It includes using assets, queues, storage buckets, and provisioning robots along with setting up roles and logging.
Topic 5
  • UiPath Document Understanding: This section of the exam measures skills of RPA developers and covers the concepts and capabilities of UiPath Document Understanding, including processing various document types, understanding rule-based and ML-based extraction, and distinguishing DU from traditional OCR.
Topic 6
  • Exception Handling: This section of the exam measures skills of RPA developers and covers structured error handling using Try Catch, Throw, Rethrow, and Retry Scope. It prepares the candidate to handle and resolve automation errors gracefully.
Topic 7
  • UiPath AI Center: This section of the exam measures skills of automation analysts and covers the basics of UiPath AI Center, its role in applying machine learning to automation, and the industries where AI models can be applied effectively.
Topic 8
  • Platform Knowledge: This section of the exam measures skills of RPA developers and covers the high-level purpose and use of UiPath platform components, including Studio, Robots, Orchestrator, and Integration Service. It also explains the difference between attended and unattended processes, providing foundational knowledge of process deployment environments.
Topic 9
  • UiPath Communications Mining - Taxonomy Design: This section of the exam measures skills of RPA developers and covers how to design a taxonomy for Communications Mining, enabling models to interpret and structure data effectively during classification and automation processes.
Topic 10
  • Debugging: This section of the exam measures skills of automation analysts and covers debugging within Document Understanding workflows. It explores the template’s architecture, exception handling, validation steps, and post-processing techniques that ensure accuracy and fault tolerance.
Topic 11
  • Variables and Arguments: This section of the exam measures skills of automation analysts and covers the creation and management of variables and arguments. It introduces key data types and explains how to apply variables and arguments across workflows to pass, store, and manipulate data.
Topic 12
  • Implementation Methodology: This section of the exam measures skills of automation analysts and covers project lifecycle knowledge, understanding key stages of implementation, and interpreting Process Design Documents (PDDs) and Solution Design Documents (SDDs).
Topic 13
  • Version Control Integration: This section of the exam measures skills of automation analysts and covers the use of Git integration in UiPath Studio for source control, including committing changes, cloning repositories, and pushing updates in collaborative environments.
Topic 14
  • Studio Interface: This section of the exam measures skills of RPA developers and covers essential navigation and setup within UiPath Studio. It includes installing Studio, connecting to Orchestrator, navigating the interface, managing packages, configuring activity settings, and publishing processes to Orchestrator.
Topic 15
  • Business Knowledge: This section of the exam measures skills of automation analysts and covers the fundamental understanding of business process automation, its value in real-world operations, and essential concepts used to identify, map, and analyze business processes.
Topic 16
  • UiPath Communications Mining - Model Training: This section of the exam measures skills of automation analysts and covers model training concepts in Communications Mining, explaining what defines a strong model and outlining the stages and components involved in developing one.

UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q123-Q128):NEW QUESTION # 123
Which property of the Get Outlook Mail Messages activity allows you to specify the number of messages to be retrieved and the order in which they are retrieved?
  • A. OrderByDate
  • B. MailFolder
  • C. Filter
  • D. Top
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The Top property in the Get Outlook Mail Messages activity is used to define:
How many emails to retrieve
The most recent emails are retrieved first (by default)
It does not directly control sort order (that's internal to Outlook's default), but limits volume.
UiPath Documentation Reference:
Get Outlook Mail Messages - UiPath Docs

NEW QUESTION # 124
What is the recommended number of documents per vendor to train the initial dataset?
  • A. 0
  • B. 1
  • C. 2
  • D. 3
Answer: D
Explanation:
According to the UiPath documentation, the recommended number of documents per vendor to train the initial dataset is 10. This means that for each vendor that provides a specific type of document, such as invoices or receipts, you should have at least 10 samples of their documents in your training dataset. This helps to ensure that the dataset is balanced and representative of the real-world data, and that the machine learning model can learn from the variations and features of each vendor's documents. Having too few documents per vendor can lead to poor model performance and accuracy, while having too many documents from a single vendor can cause overfitting and bias1.
References: 1: Document Understanding - Training High Performing Models

NEW QUESTION # 125
What is the role of connections in the UiPath Integration Service?
  • A. Connections establish tasks and exchanges between users and external applications using the authentication process of the API provider.
  • B. Connections establish tasks and exchanges between users and external applications using the authentication process of the III automation provider.
  • C. Connections establish tasks and exchanges based on a connector's compatibility with the external application.
  • D. Connections establish tasks and exchanges between users and external applications using the server- side triggers.
Answer: A
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In UiPathIntegration Service, aconnectionis the secure authentication configuration between UiPath and an external application (like Salesforce, ServiceNow, etc.). These connections rely onAPI authentication mechanismssuch as OAuth 2.0 or API Keys depending on the connector.
* They are used to enable data exchange between RPA processes and external systems.
* UiPath Documentation Reference:Integration Service - Connections

NEW QUESTION # 126
What can the Custom Named Entity Recognition out-of-the-box model be used for?
  • A. Relate customer questions to FAQ documents and automatically pull responses from these documents.
  • B. Classify text in resumes, emails, web pages, and other formats.
  • C. Understand sentiment in product reviews, customer surveys, social media posts, and emails.
  • D. Extract and classify text in emails, letters, web pages, research papers, and call transcripts.
Answer: D
Explanation:
The Custom Named Entity Recognition out-of-the-box model is a machine learning package that allows you to bring your own dataset tagged with entities you want to extract from unstructured text. The model can be trained and deployed using the UiPath AI Center, and can be integrated with the UiPath Document Understanding framework. The model can be used to extract and classify text in various domains and formats, such as emails, letters, web pages, research papers, and call transcripts. For example, you can use the model to extract information such as names, dates, addresses, amounts, products, or any other custom entity from your documents. The model supports multiple languages and can be customized according to your needs.
References: AI Center - Custom Named Entity Recognition, Custom Named Entity Recognition Documentation, UiPath AI Center - Document Understanding & Use of UiPath Custom Named Entity Recognition Model

NEW QUESTION # 127
What does the darker shading of a label prediction represent in Explore in UiPath Communications Mining?
  • A. A lower confidence score.
  • B. An incorrect prediction.
  • C. Multiple label predictions.
  • D. A higher confidence score.
Answer: D
Explanation:
In UiPath Communications Mining, the shading of label predictions in the Explore section indicates confidence levels. Darker shading represents a higher confidence score, meaning the model is more certain of the prediction made for that particular label

NEW QUESTION # 128
......
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