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UiPath Automation Solution Architect Professional v1.0 Exam Sample Questions (Q39-Q44):

NEW QUESTION # 39
In regards to UiPath Automation Cloud licensing- what happens when the Trail plan's evaluation period ends?

A. The pro Trial plan will automatically renew itself for another 60 days
B. After the trial expires; your organization will be changed for the pro plan unless you downgrade manually.
C. You need to manually choose a plan, or your UiPath cloud account will be suspended.
D. After the trial expires; your organization is automatically downgraded to the free plan.

Answer: D

Explanation:
The Pro Trial plan is a plan intended solely for internal non-production purposes, such as evaluation and testing, while fully complying with the Acceptable Use Policy outlined in the Terms of Use. It is available free of charge for a limited amount of time. You can upgrade to the Pro Trial plan if you want to experiment with more robotic power and premium services. With a Pro Trial plan, you can try the extended platform capabilities that come with a paid Pro plan. The evaluation period is limited to 60 days. After the trial expires, your organization is automatically downgraded to the Free plan1.
References:
Automation Cloud - About licensing

NEW QUESTION # 40
How can automated Test Sets be executed?

A. Only from Test Manager
B. Only from Orchestrator
C. From boll Studio and Test Manager
D. From both Orchestrator and Test Manager

Answer: D

Explanation:
Automated Test Sets can be executed from both Orchestrator and Test Manager, depending on the source and type of the test cases. Test Sets that have been linked from Orchestrator can be executed automatically or manually, if they have manual steps defined. Test Sets that have been created in Test Manager can also be executed automatically or manually, if they have test cases linked from Studio or manual steps12.
Reference:
Test Suite - Test Sets
Test Suite - Executing Tests

NEW QUESTION # 41
What are the differences between rule based and model based extractions?

A. The rule-based extraction is used for documents with a fixed format relies on rules (like regular expressions) and templates and ensures high accuracy for already known documents The model-based extraction is used tor semi-structured documents and relies on pre-trained models (like invoices receipts purchase orders etc) as well as on custom models
B. The rule-based extraction uses methods like regex extractor and forms Al. on documents with a fared format, while the model-based extraction uses the machine learning extractor on semi structured documents
C. The rub-based extraction uses methods like regex extractor and form extractor on semi-structured documents while the model based extraction uses the forma Al and machine learning on documents with fixed formal
D. The model-based extraction is used for documents with a fixed format, relies on regular expressions and templates and ensures high accuracy for already known documents The rule-based extraction is used for semi-structured documents and relies on pre-trained models as we" as on custom models

Answer: A

Explanation:
The rule-based extraction and the model-based extraction are two different methods of data extraction that target different types of documents. The rule-based extraction is suitable for structured documents that have a fixed format and layout, such as forms, tax returns, or certificates. This method relies on rules (such as regular expressions) and templates (such as position or occurrence patterns) to identify and extract the data of interest from the document. The rule-based extraction ensures high accuracy and speed for already known documents, but it requires manual configuration and maintenance of the rules and templates, and it cannot handle variations or changes in the document format. The model-based extraction is suitable for semi-structured documents that have varying formats and layouts, but contain similar types of information, such as invoices, receipts, or purchase orders. This method relies on pre-trained models (such as machine learning or artificial intelligence models) or custom models (such as user-defined models) to analyze and extract the data of interest from the document. The model-based extraction can handle variations and changes in the document format, and it can learn from feedback and improve over time, but it requires training data and validation, and it may not achieve the same level of accuracy and speed as the rule-based extraction for some documents. Reference:
Data Extraction Overview - UiPath Document Understanding
Document Processing with Improved Data Extraction | UiPath
Document Understanding - Machine Learning Extractor - UiPath

NEW QUESTION # 42
What is UiPath Al Center Typically used for?

A. To manage machine learning models exclusively.
B. To deploy and use machine learning models in RPA workflows.
C. To create machine learning models with ease.
D. To provide in-depth analysis for RPA processes and machine learning models.

Answer: B

Explanation:
UiPath AI Center is a service that allows you to integrate and automate AI models into your RPA workflows.
You can use pre-built or custom models, templates, and a drag-and-drop interface to deploy, manage, and improve your AI-enhanced automations. You can also consume the models within Studio or Orchestrator using the ML Skill activity or the ML Extract activity.
References:
RPA & AI Integration with AI Center
AI Center - About AI Center
How to use UiPath AI Center for Object Detection

NEW QUESTION # 43
What is the definition of Artificial intelligence?

A. Artificial intelligence is an area of machine learning concerned with artificial neural networks. These are a series of algorithms that aim to recognize relationships in a set of data through a process that mimes biological neural networks.
B. Artificial intelligence is a machine learning technology that gives computer the ability to interpret, manipulate, and comprehend human language.
C. Artificial intelligence is the theory and development of computer system that are able to perform tasks that normally require human intelligence and decision making.
D. Artificial intelligence is a field of computer science that focuses on enabling computers to identify and understand objects and people in images and videos. It can be seen as the eyes that enable the computer to observer and understand

Answer: C

Explanation:
Artificial intelligence (AI) is a broad term that covers various technologies that enable machines to perform tasks that traditionally require human intelligence, such as reasoning, learning, problem-solving, and using language. AI can be classified into different types, such as weak AI, strong AI, and artificial general intelligence (AGI), depending on the level of intelligence and the scope of tasks that the machines can perform2. Some of the common applications of AI include natural language processing, computer vision, speech recognition, machine learning, and deep learning3.
Reference:
1: Artificial intelligence (AI) | Definition, Examples, Types, Applications, Companies, & Facts | Britannica
2: What Is Artificial Intelligence? Definition, Uses, and Types | Coursera
3: What is Artificial Intelligence (AI) ? | IBM

NEW QUESTION # 44
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