UiPath-SAIv1 Exam Practice Test Instant Access

Question 1

Which validation checks are performed for ML packages uploaded with the Enable Training option inactive?

AExistence of a non-empty root folder, requirements.txt file, and train.py file in the root folder which implements a class Main. The class is further validated to implement an__init_function.

BExistence of a non-empty root folder, requlrements.txt file, and main.py file in the root folder which implements a class Main. The class is further validated to implement an__init and a predict function.

CExistence of a non-empty root folder, main.py file in the root folder which implements a dass Main. The class is further validated to implement an__init__and a predict function.

DExistence of a requirements.txt file, and main.py file which implements a class Main. The class is further validated lo implement an__init__and a predict function.

Answer : B

When uploading an ML package in UiPath AI Center with the Enable Training option inactive, several validation checks are performed:

There must be a non-empty root folder.

A requirements.txt file must be present to define dependencies.

A main.py file should be in the root folder, which implements a class Main.

The class must implement the necessary methods, such as __init__ and predict.

For more details, refer to:

UiPath AI Center Documentation: ML Package Validation

Question 2

How do you use the Generative Classifier within UiPath Document Understanding Cloud APIs to classify a document as either an "Invoice" or a "Receipt"?

ABy sending a GET request to /api/framework/projects/{projectld}/classifiers/generative_classifier/classification with a body containing prompts that specify the 'Invoice' and 'Receipt' names and descriptions.

BBy sending a POST request to yapi/framework/projectsy{projectld}/ctassifiers/generative_classifier/classification with a body containing prompts that specify the 'Invoice' and 'Receipt' names and descriptions.

CBy sending a PUT request to /api/framework/proiects/{projectld}/classifiers/generative_classifier/classification without any specific classification details in the body of the request.

DBy sending a POST request to /api/framework/projects/{projectld}/classifiers/generative_classifier/dassification with a body containing prompts that specify the 'Invoice' and 'Receipt' names and a description for their fields.

Answer : B

In UiPath Document Understanding Cloud APIs, the Generative Classifier is used to classify documents by leveraging a generative AI model. To classify a document as either an 'Invoice' or a 'Receipt,' a POST request must be sent to the /api/framework/projects/{projectId}/classifiers/generative_classifier/classification endpoint. The body of this request should contain prompts specifying the classification types (in this case, 'Invoice' and 'Receipt') along with their corresponding descriptions. This allows the model to correctly classify incoming documents based on these predefined prompts.

For further reading, refer to:

UiPath Document Understanding API Documentation: Cloud API for Classification

Generative Classifier APIs: UiPath Classification APIs

Question 3

Which UiPath product is most suitable for processing invoices?

AUiPath Communications Mining.

BUiPath Task Mining.

CUiPath Process Mining.

DUiPath Document Understanding.

Answer : D

UiPath Document Understanding is the most suitable product for processing invoices. It provides tools for digitization, classification, data extraction, and validation, which are ideal for structured and semi-structured documents like invoices.

Question 4

What does a UiPath Communications Mining taxonomy include?

AGeneral fields and datasets.

BLabels and sources.

CMessages, labels, and general fields.

DLabels and general fields.

Answer : D

In UiPath Communications Mining, a taxonomy includes labels (used to classify messages) and general fields (used to extract specific pieces of information from messages). These components allow effective categorization and data extraction.

Question 5

What fields are available when creating an Al Center project?

AName, description, and labels.

BName, description, and permissions.

CName and description.

DName and labels.

Answer : C

When creating an AI Center project in UiPath, the fields available to input are the project's name and description. These fields allow you to clearly label and describe the purpose of the AI project within the UiPath platform. Permissions and labels can be managed separately after the project is created

Question 6

Why is it important to gather and analyze data about the languages in scope?

AThe main reason is that all taxonomy fields should have their names translated into all the languages presented in the documents to be processed.

BDifferent Document Understanding components have support for different languages, so they have to be selected according to the requirements.

CThis is a standard check but has no actual effect on the Document Understanding process.

DIf an ML (Machine Learning) extractor is used, the model schema fields should be renamed according to the most frequently used language from the documents to be processed

Answer : B

It is essential to analyze the languages involved in a project because different components of UiPath's Document Understanding framework have varying language support. For instance, some OCR engines and classifiers support specific languages, and this determines whether a particular language can be processed accurately. As the supported languages differ across components such as the Machine Learning Extractor, Form Extractor, and various OCR services, selecting the right components is crucial to meeting project requirements

Question 7

What new capability has been introduced for processing unstructured documents in the 2023.10 release?

AReal-time document translation.

BOnly using pre-trained extraction models.

CManual classification of document types.

DGenerative capabilities for classifying various document types.

Answer : D

In the 2023.10 release of UiPath, a significant new feature is the introduction of generative capabilities for classifying various document types. This update allows for more advanced handling of unstructured data by leveraging AI to automatically generate classifications, even for document types that the model hasn't encountered before. This feature enhances the flexibility and power of Document Understanding, enabling organizations to handle a wider variety of documents without needing extensive manual setup for each new type.

(Source: UiPath 2023.10 Release Notes)

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