UiPath-SAIv1 Exam Practice Test Instant Access

Question 1

What is the role of the Taxonomy Manager?

ATo select which extractors are trained for each document type and field.

BTo present a document processing specific user interface for validating and correcting automatic classification outputs.

CTo create and edit a Taxonomy file specific to the current automation project.

DTo select the type of ML that can be used in the project.

Answer : C

The Taxonomy Manager is used to create and edit a taxonomy file that defines the structure of the documents to be processed. It specifies document types, categories, and the fields that need to be extracted, forming the foundation for document processing workflows.

Question 2

How long does the typical Machine Learning model deployment process take in UiPath AI Center?

ALess than 5 minutes.

BBetween 5 and 10 minutes.

CBetween 10 and 15 minutes.

DMore than 15 minutes.

Answer : C

The typical machine learning model deployment process in UiPath AI Center usually takes between10-15 minutes1.This process involves wrapping the model in UiPath's serving framework and deploying it within a namespace on AI Fabric's Kubernetes cluster that is only accessible by your tenant1. Please note that the actual time may vary depending on the complexity of the model and other factors.

AI Center - Managing ML Skills (uipath.com)

Question 3

What is the definition of Deep Learning?

AA sub-field of artificial intelligence that enables systems to learn from data.
Systems learn from previous experience and information to deduce and predict future information. To do this they use algorithms that learn to perform a specific task without being explicitly programmed.

BThe theory and development of computer systems that are able to perform tasks that normally require human intelligence and decision making.

CA field of artificial intelligence that enables computers to gain high-level understanding from digital images or videos. If AI is the brain, then this is the eye that enables the computer to observe and understand. It works the same as the human eye.

DAn 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 mimics biological neural networks.

Answer : D

Deep learning is a subset of machine learning that uses multiple layers of artificial neural networks to learn from data and perform complex tasks. The term ''deep'' refers to the number of layers in the network, which can range from a few to hundreds or even thousands. Each layer consists of a set of nodes that perform mathematical operations on the input data and pass the output to the next layer. The network learns by adjusting the weights of the connections between the nodes based on the feedback from the desired output. Deep learning can handle various types of data, such as images, text, speech, or video, and can automatically extract features and patterns from them without human intervention.Deep learning is behind many applications of artificial intelligence, such as computer vision, natural language processing, speech recognition, and generative models123.

References:1: What is Deep Learning?| IBM2: What Is Deep Learning?Definition, Examples, and Careers | Coursera3: Deep learning - Wikipedia

Question 4

What rule should be used in Taxonomy Manager for a text field that can have one of multiple known values?

AEnds with

BContains

CPossible values

DStarts with

Answer : C

In UiPath's Taxonomy Manager, the 'Possible values' rule should be used when a text field can have one of several predefined values. This ensures that the extracted data is validated against a list of acceptable values, helping to maintain consistency and accuracy during the extraction process. It is particularly useful for fields such as status indicators or categorical fields where only a limited set of options is valid.

(Source: UiPath Taxonomy Manager documentation)

Question 5

Why is having high coverage important for an automation-focused use case in UiPath Communications Mining?

AThe higher the coverage, the lower the model's recall, resulting in greater throughput of automatable processes.

BHigh coverage ensures that the software consumes less computational resources, resulting in cost savings for the organization implementing the automation.

CHigh coverage on the model means that fewer communications will be sent for manual review and that fewer automatable processes are missed.

DWith high coverage, you can increase the amount of data provided downstream via Streams.

Answer : C

In UiPath Communications Mining, high coverage ensures that a larger proportion of communications is classified with meaningful labels, meaning fewer communications are sent for manual review and more processes are captured for automation. This leads to more effective automation, reducing the need for human intervention and ensuring that the automation use case is fully realized.

For more details, refer to:

UiPath Communications Mining Performance Metrics: Coverage and Automation

Question 6

Which statement accurately describes out-of-the-box models in UiPath?

AOut-of-the-box models are custom-built models created specifically for each project.

BOut-of-the-box models are pre-trained models that cover a wide range of document types.

COut-of-the-box models require extensive training and customization before they can be used effectively.

DOut-of-the-box models are only available for specific languages and cannot be adapted for multilingual documents.

Answer : B

UiPath provides out-of-the-box pre-trained models that are ready for use and cover a wide variety of document types. These models can be used as-is for common use cases or fine-tuned based on specific requirements, making them versatile for different projects

Question 7

What is the definition of Machine Learning?

AAn 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 mimics biological neural networks.

BThe theory and development of computer systems that are able to perform tasks that normally require human intelligence and decision making.

CA sub-field of artificial intelligence that enables systems to learn from data. Systems learn from previous experience and information to deduce and predict future information. To do this they use algorithms that learn to perform a specific task without being explicitly programmed.

DA branch of artificial intelligence that deals with analyzing, understanding, and generating human natural languages. For example, NLP enables computers to hear speech, read text, interpret the text/speech or measure the sentiment.

Answer : C

Machine Learning is a sub-field of artificial intelligence that allows systems to learn from data and improve over time without being explicitly programmed. It leverages algorithms to deduce and predict outcomes based on prior experiences and information.

UiPath Certified Professional Specialized AI Professional v1.0 UiPath-SAIv1 Exam Practice Test