UiPath-ABAv1 Exam Dumps : UiPath Certified Professional Automation Business Analyst Professional v1.0

The UAT (User Acceptance Testing) planning phase in RPA defines a crucial stage where a plan is developed for testing UiPath robots by end-users to ensure they meet the business requirements and perform as expected. This phase is essential for validating the functionality and reliability of the automation before it goes live.

In the context of UiPath Cloud Platform, training a machine learning (ML) model using a GPU (Graphics Processing Unit) is significantly faster than using a CPU (Central Processing Unit). This is because GPUs are designed to handle parallel processing, which is highly beneficial for the matrix and vector computations required in ML model training. GPUs can perform more calculations simultaneously compared to CPUs, leading to faster training times, especially with large and complex datasets1.

The UiPath documentation specifically recommends using GPU training for large and production datasets, as CPU training is much slower and should be used sparingly, for small datasets for demo or testing purposes1. This aligns with the general understanding that for deep learning training, GPUs should be used due to their significant speed advantage over CPUs23.

In the context of UiPath's Change Control Process:

Categorization: Changes are categorized as Low, Medium, or High based on the time and resources required for implementation.

Low: Typically involves minor adjustments with minimal impact, requiring fewer resources and less time.

Medium: Changes that involve moderate effort, such as adjustments to existing automations.

High: Significant changes that require a longer duration, extensive testing, and resource involvement.

Effort Calculation: The company decides the duration for each category, e.g., Low (<2 days), Medium (2–5 days), High (>5 days).

Alignment with Change Management Principles: These categories ensure clear communication, effective planning, and prioritization during the change request and implementation stages​.