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UiPath Specialized AI Associate Exam (2023.10) exam prep material & UiPath-SAIAv1 useful exam pdf & UiPath Specialized AI Associate Exam (2023.10) exam practice questions

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UiPath UiPath-SAIAv1 Exam Syllabus Topics:

Topic
Details

Topic 1

Debugging: This section of the exam measures skills of automation analysts and covers debugging within Document Understanding workflows. It explores the template’s architecture, exception handling, validation steps, and post-processing techniques that ensure accuracy and fault tolerance.

Topic 2

Data Manipulation: This section of the exam measures skills of RPA developers and covers data handling with VB.Net string functions, RegEx patterns, arrays, lists, and dictionaries. It also covers DataTable operations such as building, filtering, and converting data for automation.

Topic 3

Environments, Applications, and
or Tools: This section of the exam measures skills of RPA developers and covers the candidate’s comfort level with common development tools, platforms, and environments such as Excel, Outlook, browsers, version control, Studio, Document Understanding Template, AI Center, and Communication Mining.

Topic 4

Control Flow: This section of the exam measures skills of RPA developers and covers debugging methods and logic handling in projects. It introduces the use of breakpoints, tracepoints, and debugging panels for managing and improving workflow execution.

Topic 5

UiPath AI Center: This section of the exam measures skills of automation analysts and covers the basics of UiPath AI Center, its role in applying machine learning to automation, and the industries where AI models can be applied effectively.

Topic 6

UiPath Studio - Document Understanding Activities: This section of the exam measures skills of RPA developers and covers configuring document classification and extraction workflows using Studio activities, taxonomy management, digitization, and validation tools. It also includes the use of trained ML models and prebuilt extractors.

Topic 7

Integration Service: This section of the exam measures skills of automation analysts and covers the use of UiPath Integration Service, its connectors, and triggers, showing how these elements enable smooth interaction between UiPath and third-party systems.

Topic 8

Email Automation: This section of the exam measures skills of RPA developers and covers automating email processes using Microsoft 365 and Gmail integrations. It focuses on sending, receiving, and managing emails as part of workflow automation.

Topic 9

Platform Knowledge: This section of the exam measures skills of RPA developers and covers the high-level purpose and use of UiPath platform components, including Studio, Robots, Orchestrator, and Integration Service. It also explains the difference between attended and unattended processes, providing foundational knowledge of process deployment environments.

Topic 10

Workflow Analyzer: This section of the exam measures skills of RPA developers and covers using Workflow Analyzer and validation tools to identify errors, maintain project compliance, and ensure workflow efficiency during development.

Topic 11

UiPath Document Understanding Framework: This section of the exam measures skills of automation analysts and covers how to apply the Document Understanding Framework, use templates, and develop proof-of-concept components. It focuses on building workflows for document processing.

Topic 12

Exception Handling: This section of the exam measures skills of RPA developers and covers structured error handling using Try Catch, Throw, Rethrow, and Retry Scope. It prepares the candidate to handle and resolve automation errors gracefully.

Topic 13

Logging: This section of the exam measures skills of automation analysts and covers interpretation of robot execution logs and the application of logging best practices to support auditability, diagnostics, and monitoring.

Topic 14

UiPath Communications Mining - Taxonomy Design: This section of the exam measures skills of RPA developers and covers how to design a taxonomy for Communications Mining, enabling models to interpret and structure data effectively during classification and automation processes.

Topic 15

Working with Files and Folders: This section of the exam measures skills of automation analysts and covers creating and managing files and folders within local directories, including iteration and file manipulation using Studio activities.

Topic 16

Version Control Integration: This section of the exam measures skills of automation analysts and covers the use of Git integration in UiPath Studio for source control, including committing changes, cloning repositories, and pushing updates in collaborative environments.

Topic 17

Studio Interface: This section of the exam measures skills of RPA developers and covers essential navigation and setup within UiPath Studio. It includes installing Studio, connecting to Orchestrator, navigating the interface, managing packages, configuring activity settings, and publishing processes to Orchestrator.

Topic 18

Variables and Arguments: This section of the exam measures skills of automation analysts and covers the creation and management of variables and arguments. It introduces key data types and explains how to apply variables and arguments across workflows to pass, store, and manipulate data.

Topic 19

UiPath Communications Mining - Model Training: This section of the exam measures skills of automation analysts and covers model training concepts in Communications Mining, explaining what defines a strong model and outlining the stages and components involved in developing one.

Topic 20

UiPath Document Understanding: This section of the exam measures skills of RPA developers and covers the concepts and capabilities of UiPath Document Understanding, including processing various document types, understanding rule-based and ML-based extraction, and distinguishing DU from traditional OCR.

Topic 21

Updates Introduced to 2023.10: This section of the exam measures skills of automation analysts and covers the most recent product updates in UiPath, including one-click classification and extraction, Generative AI features, and enhancements to validation, annotation, and workflow design.

Topic 22

UiPath Communications Mining: This section of the exam measures skills of RPA developers and covers the application of Communications Mining in automation and analytics. It distinguishes this capability from Task Mining and Process Mining, explains the interface, and describes use cases.

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q141-Q146):

NEW QUESTION # 141
What components are part of the Document Understanding Process template?

A. Import, Classification, Text Extractor, and Data Validation
B. Load Taxonomy, Digitization, Classification, Data Extraction, and Data Validation Export
C. Load Document, Categorization, Data Extraction, and Validation
D. Load Taxonomy, Digitization, Categorization, Data Validation, and Export

Answer: B

Explanation:
Reference: UiPath Document Understanding

NEW QUESTION # 142
What should a UiPath Communications Mining taxonomy contain when it is being imported?

A. Label predictions.
B. Entity descriptions.
C. Label descriptions.
D. Entity predictions.

Answer: C

Explanation:
According to the UiPath documentation, a UiPath Communications Mining taxonomy is a collection of all the labels applied to the verbatims in a dataset, structured in a hierarchical manner. Labels are the concepts and intents that you want to capture in the dataset to suit your specific objectives. When you import your taxonomy from a spreadsheet, you need to provide the label descriptions, which are the names of the labels and their level in the hierarchy. Label predictions and entity predictions are the outputs of the model training process, and they are not part of the taxonomy. Entity descriptions are the definitions of the entities that you want to extract from the verbatims, and they are not part of the taxonomy either.
References:
Communications Mining - Taxonomies
Communications Mining - Importing your taxonomy
Communications Mining - Building your taxonomy structure

NEW QUESTION # 143
A project contains a Try Catch activity in the "Main.xaml" workflow. In the Catches block, there is a Rethrow activity. The process is started from Orchestrator and an exception is caught in the Trysection. What is the expected result?

A. Exception Pop-up is displayed on the robot machine.
B. Job is completed with a "Stopped" state.
C. Job is completed with a "Faulted" state.
D. Job is completed with a "Successful" state.

Answer: C

Explanation:
Reference: UiPath Try Catch and Rethrow

NEW QUESTION # 144
What are the languages supported by the generic Document Understanding ML Package?

A. Languages using the Latin alphabet (like Italian, French. Portuguese. Spanish, and Romanian), and the Greek left-to-right alphabet.
B. Languages using the Greek left-to-right alphabet. Japanese, and Chinese.
C. Languages using the Latin alphabet, the Cyrillic alphabet, the Greek left-to-right alphabet. Japanese, and Chinese.
D. Languages using the Cyrillic alphabet, the Greek left-to-right alphabet, and Chinese.

Answer: C

Explanation:
According to the UiPath documentation1, the generic Document Understanding ML Package supports data extraction from any type of structured or semi-structured documents, building an ML model from scratch. The supported languages for this package are Latin-based languages, Cyrillic languages, Greek left-to-right, and Japanese (Preview). Additionally, the documentation23 also mentions that the package can support Chinese with the use of an OCR that supports that language. Therefore, the correct answer is D.
References: Document Understanding - Supported Languages, Document Understanding - ML Packages, Document Understanding - ML Packages.

NEW QUESTION # 145
In the general fields training, what actions does the Communications Mining Train feature guide you through?

A. It guides you right from the moment you create a dataset with the next best action to take to advance your general fields training.
B. It guides you to start entity training without a dataset.
C. It guides you to focus solely on model refinement.
D. It guides you through the completion of model training before starling entity training.

Answer: A

Explanation:
his is confirmed in the UiPath documentation, where the "Train" feature guides users from the dataset creation stage through the necessary steps to optimize the training process. The system recommends next best actions based on progress to ensure efficient and focused training

NEW QUESTION # 146
......

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