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問題 #18
What are the main stages of an Assisted Task Mining project?
答案：C
解題說明：
Understanding Assisted Task Mining (ATM):
Assisted Task Mining empowers the Business Analyst to collaborate with Subject Matter Experts (SMEs) and capture known tasks for automation. This involves collecting data from real-time actions, analyzing it with AI, visualizing the results, and exporting insights for process optimization.
Why Option A is Correct:
Collect Data: This involves capturing real-time actions such as clicks, keystrokes, and screens during task execution.
Analyze with AI: The collected data is processed using AI to identify patterns and variations within the task.
Visualize Results: Results are presented as task maps or workflows to understand processes holistically.
Export Results: The insights can be exported to create a Process Definition Document (PDD) or automation skeleton in UiPath Studio.
Why Other Options Are Incorrect:
Option B: Extracting permissions and managing projects are not core stages in ATM.
Option C: Recording all applications and ROI focus are more aligned with Unassisted Task Mining.
Option D: Exporting actions and generating dashboards are not typical ATM stages.
問題 #19
For your trigger you want to set some non-working days restrictions based on a Calendar Where should you define such a calendar?
答案：C
解題說明：
Non-working days restrictions based on a calendar should be defined at the Tenant level in UiPath Orchestrator. This allows for the management of non-working days across multiple processes and departments within the same tenant. Once defined, these calendars can be applied to triggers to ensure that automation jobs respect the non-working days settings1.
References: The process for managing non-working days and applying them to triggers is detailed in the UiPath Documentation Portal, specifically in the section "Managing Non-Working Days" found at
https://docs.uipath.com/orchestrator/automation-cloud/latest/user-guide/managing-non-working-days1.
問題 #20
What is the difference between Data Labeling and Document Manager?
答案：C
解題說明：
The difference between Data Labeling and Document Manager is that Data Labeling is used to annotate documents that have been previously uploaded into Document Manager. While Document Manager serves as a repository and management system for documents, Data Labeling involves the process of marking these documents to train machine learning models for better data extraction.
Reference: UiPath Documentation on Data Labeling and Document Manager at https://docs.uipath.com/.
問題 #21
Is it possible to use a third-party ML model with AI Center?
答案：C
解題說明：
UiPath AI Center provides flexibility for integrating third-party ML models into its framework. Here's how:
Third-Party Model Integration: Users can create a custom package for AI Center that incorporates a third-party model. This involves exporting the model in a compatible format (e.g., ONNX or TensorFlow SavedModel) and wrapping it into a package deployable in AI Center.
Scenarios for Usage: This is especially useful when businesses already have proprietary models developed externally or sourced from other vendors. These can be fine-tuned and deployed alongside UiPath's RPA workflows.
Infrastructure Consideration: While deploying on-premises provides better control over model usage and performance, AI Center supports GPU acceleration and third-party model integration across different deployment modes, ensuring scalability and processing efficiency.
This approach allows businesses to maintain the versatility of their ML pipelines and integrate advanced analytics with minimal disruption to their existing automation setup.
問題 #22
What is the purpose of human in the loop?
答案：C
解題說明：
"Human in the loop" is a core concept in UiPath automation solutions, where automation might require human input or decisions to complete a task. Specifically, UiPath defines it as:
"Human-in-the-loop (HITL) involves incorporating human validation steps within an automated workflow to manage exceptions, validate data, or make decisions that require human judgment." This concept is a fundamental part of processes that require human expertise or compliance checks, typically seen in document processing, data extraction, and exception handling.
References:
UiPath Action Center documentation: Human-in-the-loop Automation
UiPath Automation Business Analyst training resources.
問題 #23
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