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UiPath UiPath-SAIAv1 Exam Syllabus Topics:TopicDetailsTopic 1

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 2

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 3

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 4

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.

Topic 5

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 6

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 7

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 8

Orchestrator: This section of the exam measures skills of RPA developers and covers Orchestrator's structure and functionality, including entities at the tenant and folder level. It includes using assets, queues, storage buckets, and provisioning robots along with setting up roles and logging.

Topic 9

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 10

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 11

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 12

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 13

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 14

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 15

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 16

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 17

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 18

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 19

Business Knowledge: This section of the exam measures skills of automation analysts and covers the fundamental understanding of business process automation, its value in real-world operations, and essential concepts used to identify, map, and analyze business processes.

Topic 20

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 21

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 22

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 23

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 24

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.

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q96-Q101):

NEW QUESTION # 96
What is the minimum number of pinned examples users should provide per label in UiPath Communications Mining?

A. 0
B. 1
C. 2
D. 3

Answer: B

Explanation:
Mining, it is recommended that users provide a minimum of 25 pinned examples per label to ensure proper training and accurate predictions by the machine learning models. This number allows the platform to have a sufficient variety of examples to generalize and make reliable predictions for each label in real-world scenarios.
The minimum number of pinned examples per label is crucial because it enhances both precision and recall, helping the model effectively differentiate between labels and improving overall model performance. If fewer examples are provided, the model may struggle with generalization and might not perform well in distinguishing between similar or overlapping categories.
This standard of 25 pinned examples is outlined in several UiPath documentation sections and best practices for training models in Communications Mining UiPath Documentation UiPath Documentation UiPath Community Forum For further details, refer to UiPath's official Communications Mining User Guide on their documentation portal.

NEW QUESTION # 97
When training labels and general fields in UiPath Communications Mining, what is the recommended approach to training efficiency?

A. Train only general fields for faster results.
B. Train general fields first, then labels.
C. Focus on labels, and general fields will be trained automatically.
D. Train both labels and general fields at the same time.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The recommended practice in Communications Mining is to train both labels and general fields simultaneously. This ensures the system learns the relationships and intent expressions effectively.
This approach helps improve the overall model accuracy by leveraging training signals from both classification and field extraction.
UiPath Documentation Reference: UiPath Communications Mining Documentation - Labeling Strategy

NEW QUESTION # 98
Where should a model be pinned in UiPath Communications Mining?

A. On the models tab.
B. In Admin > Models.
C. When setting up a stream.
D. In the validation page.

Answer: A

Explanation:
According to UiPath documentation, model versions can be pinned and managed on the "models" tab, ensuring that users can maintain and revert to specific versions when necessary for continuity and performance

NEW QUESTION # 99
What are the three types of classifier trainers available in packages UiPath.lntelligentOCR.Activities and UiPath.DocumentUnderstanding.ML.Activities?

A. Intelligent Keyword Classifier Trainer, Language Based Classifier Trainer, and Image Based Classifier Trainer.
B. Image Based Classifier Trainer, Format Based Classifier Trainer, and Machine Learning Classifier Trainer.
C. Keyword Based Classifier Trainer, Intelligent Keyword Classifier Trainer, and Machine Learning Classifier Trainer.
D. Machine Learning Classifier Trainer, Language Based Classifier, and Keyword Based Classifier Trainer.

Answer: C

Explanation:
UiPath provides three types of classifier trainers to optimize document classification: Keyword Based Classifier Trainer, Intelligent Keyword Classifier Trainer, and Machine Learning Classifier Trainer. These trainers are used to teach the system how to categorize documents based on keywords, intelligent learning patterns, or machine learning techniques for more complex classifications.(Source: UiPath Classifier Trainer documentation

NEW QUESTION # 100
Which of the following options is accepted as a Column field name in Document Manager?

A. first_n@me
B. f1rst-name
C. first name
D. First_name123

Answer: D

Explanation:
According to the UiPath documentation, the field name for a column field in Document Manager does not accept uppercase letters. It can only contain lowercase letters, numbers, underscore _ and dash -12. Therefore, the only option that meets these criteria is D. First_name123. The other options are invalid because they either contain uppercase letters, spaces, or @ symbols, which are not allowed.
References: 1: Document Understanding - Create and Configure Fields 2: Document Understanding - Create
& Configure Fields

NEW QUESTION # 101
......

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