Question # 1
What is the Machine Learning Extractor? |
A. A specialized model that can recognize multiple languages in the same document using
API calls to a Hugging Face model with over 250 languages. | B. An extraction model that can be enabled and trained in Al Center. For better accuracy.
25 documents per model are recommended to train the model. | C. A tool using machine learning models to identify and report on data targeted for data
extraction. | D. A tool that helps extract data from different document structures, and is particularly
useful when the same document has multiple formats. |
D. A tool that helps extract data from different document structures, and is particularly
useful when the same document has multiple formats.
Question # 2
Which of the following are unstructured documents? |
A. Invoices, receipts, purchase orders, and medical bills. | B. Banking forms, tax forms, surveys, and identity cards. | C. Contracts, emails, banking forms, and tax forms. | D. Contracts, agreements, and emails. |
D. Contracts, agreements, and emails.
Explanation: Unstructured documents are those that do not have a predefined format or
layout, and therefore cannot be easily processed by traditional methods. They often contain
free-form text, images, tables, and other elements that vary from document to document.
Examples of unstructured documents include contracts, agreements, emails, letters,
reports, articles, and so on. UiPath Document Understanding is a solution that enables the
processing of unstructured documents using AI-powered models and RPA workflows1.
The other options are not correct because they are examples of structured or semistructured
documents. Structured documents are those that have a fixed format or layout,
and can be easily processed by rules-based methods. They often contain fields, labels, and values that are consistent across documents. Examples of structured documents include
banking forms, tax forms, surveys, identity cards, and so on. Semi-structured documents
are those that have some elements of structure, but also contain variations or unstructured
content. They often require a combination of rules-based and AI-powered methods to
process. Examples of semi-structured documents include invoices, receipts, purchase
orders, medical bills, and so on2.
Question # 3
What is the correct order of uploading a package exported from UiPath AI Center?
Instructions: Drag the steps found on the "Left" and drop them on the "Right" in the correct
order.
 |
 Explanation:
Export the package from AI Center. This is the first step where you prepare the
package to be moved.
On the ML Packages page, click the Import ML Package button. This step is where
you start the process of importing the package you've exported.
On the Upload package field, add the zip file downloaded using the Downloading
ML Packages procedure. After starting the import process, you will upload the
actual package.
Click Create. This is the final step where you finalize the uploading process of your
ML package.
Please proceed with these steps in the UiPath AI Center to upload your exported package
correctly.
Question # 4
Which environment variable is relevant for Evaluation pipelines? |
A. eval.enable_ocr | B. eval.redo_ocr | C. eval.enable_qpu | D. eval.use_cuda |
B. eval.redo_ocr
Explanation: The environment variable eval.redo_ocr is relevant for Evaluation pipelines because it allows you to rerun OCR when running the pipeline to assess the impact of OCR
on extraction accuracy. This assumes an OCR engine was configured when the ML
Package was created. The other options are not valid environment variables for Evaluation
pipelines.
Question # 5
What is the name of the web application that allows users to prepare, review, and make
corrections to datasets required for Machine Learning models? |
A. Document Manager. | B. Digitization. | C. Data Manager. | D. ML Extractor. |
C. Data Manager.
Explanation: Data Manager is a web application that allows users to prepare, review, and
make corrections to datasets required for Machine Learning models. Data Manager
enables users to create and manage datasets, label data, validate and export data, and
monitor data quality and progress. Data Manager supports various types of data, such as
documents, images, text, and tables. Data Manager is integrated with AI Center, where
users can train and deploy Machine Learning models using the datasets created or
modified in Data Manager12.
Question # 6
What is the correct execution order of the Document Understanding template stages?
Instructions: Drag the stages found on the "Left" and drop them on the "Right” in the correct
order.
 |
Question # 7
How can the code be tested in a development or testing environment in the context of the
Document Understanding Process? |
A. Use them as a template to create other tests. | B. Simply run the existing tests | C. Based on the use case developed, create test data to test existing and new tests. | D. Based on the use case developed, create test data to test existing tests. |
C. Based on the use case developed, create test data to test existing and new tests.
Explanation: According to the UiPath Document Understanding Process template, the
best way to test the code in a development or testing environment is to create test data
based on the use case developed, and use it to test both the existing and the new tests.
The test data should include different document types, formats, and scenarios that reflect
the real-world data that the process will handle in production. The existing tests are
provided by the template and cover the main functionalities and components of the
Document Understanding Process, such as digitization, classification, data extraction,
validation, and export. The new tests are created by the developer to test the
customizations and integrations that are specific to the use case, such as custom
extractors, classifiers, or data consumption methods. The test data and the test cases should be updated and maintained throughout the development lifecycle to ensure the
quality and reliability of the code.
Question # 8
What is one of the purposes of the Config file in the UiPath Document Understanding
Template? |
A. It contains the configuration settings for the UiPath Robot and Orchestrator integration. | B. It stores the API keys and authentication credentials for accessing external services. | C. It specifies the output file path and format for the processed documents. | D. It defines the input document types and formats supported by the template. |
B. It stores the API keys and authentication credentials for accessing external services.
Explanation: The Config file in the UiPath Document Understanding Template is a JSON
file that contains various parameters and values that control the behavior and functionality
of the template. One of the purposes of the Config file is to store the API keys and
authentication credentials for accessing external services, such as the Document
Understanding API, the Computer Vision API, the Form Recognizer API, and the Text
Analysis API. These services are used by the template to perform document classification,
data extraction, and data validation tasks. The Config file also allows the user to customize
the template according to their needs, such as enabling or disabling human-in-the-loop
validation, setting the retry mechanism, defining the custom success logic, and specifying
the taxonomy of document types.
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UiPath Certified Professional Specialized AI Professional v1.0 Test Dumps
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Exam Name: UiPath Certified Professional Specialized AI Professional v1.0
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Questions People Ask About UiPath-SAIv1 Exam
The exam covers the following key areas:
- 1. UiPath Document Understanding
- 2. AI Center and Machine Learning models
- 3. Integration of AI capabilities into automation workflows
- 4. Data extraction and processing using AI
- 5. Best practices for AI-driven automation
To prepare for the exam:
-
1. Take the UiPath AI Developer Training.
-
2. Practice integrating AI capabilities into automation workflows.
-
3. Take practice test.
-
4. Use UiPath Academy’s free learning resources.
-
5. Review the official UiPath SAIv1 Exam Guide.
- 1. Be proficient in using Document Understanding for data extraction.
- 2. Learn how to integrate AI capabilities into automation workflows.
- 3. Understand how to use AI Center for managing machine learning models.
- 4. Familiarize yourself with best practices for AI-driven automation.
- 5. Allocate time wisely during the exam to answer all questions.
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