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UiPath-SAIAv1 Exam Questions
- Topic 1: 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 2: 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 3: 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 4: 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 5: 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 6: 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 7: 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 8: 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 9: 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 10: 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 11: 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 12: 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 13: 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 14: Implementation Methodology: This section of the exam measures skills of automation analysts and covers project lifecycle knowledge, understanding key stages of implementation, and interpreting Process Design Documents (PDDs) and Solution Design Documents (SDDs).
- Topic 15: 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 16: 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 17: 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 18: 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 19: 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 20: 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 21: 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 22: 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 23: 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 24: 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 25: 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.
Free UiPath UiPath-SAIAv1 Exam Actual Questions
Note: Premium Questions for UiPath-SAIAv1 were last updated On Aug. 10, 2025 (see below)
Which is the most suitable extractor for extracting data from invoices from different customers?
Comprehensive and Detailed Explanation From Exact Extract:
The Machine Learning Extractor is best suited for handling semi-structured documents like invoices, which often vary by layout, format, and provider. Unlike template-based extractors, ML extractors learn from data and generalize across multiple formats.
It is trained to recognize fields regardless of positioning or formatting, making it ideal for vendor invoices, receipts, and more.
UiPath Documentation Reference:
Choosing the Right Extractor -- UiPath DU
As a best practice, who should perform the data labeling?
As a best practice, Subject Matter Experts (SMEs) should perform the data labeling in UiPath Communications Mining or Document Understanding projects. SMEs have the in-depth knowledge of the specific content and context, which ensures that the data is labeled correctly and meaningfully for training machine learning models. Their expertise is essential for accurate taxonomy and data preparation
What is the primary objective of the UiPath Document Understanding (DU) process template?
Comprehensive and Detailed Explanation From Exact Extract:
The main purpose of Document Understanding is to help developers extract structured information from unstructured documents (invoices, receipts, forms, etc.) using AI and OCR.
It streamlines the entire pipeline of digitizing, classifying, extracting, and validating document data.
UiPath Documentation Reference:
Document Understanding Overview
Which UiPath Studio activity creates a Data Labeling Action in UiPath Action Center?
Which are all the options for managing ML Skills?
In UiPath AI Center, ML Skills can be managed in various ways, allowing users to customize and control how these skills are deployed and used. The management options include:
Creating a new ML skill.
Stopping a deployed skill.
Redeploying an ML skill.
Updating to a new package version.
Rolling back to a previous version if needed.
Modifying GPU usage.
Modifying the use of AI units.
Making the skill public or private.
Deleting an ML skill when no longer needed.
This provides flexibility for both managing the ML infrastructure and optimizing resources in real-time.
For more details, refer to:
UiPath AI Center Documentation: Managing ML Skills
ML Skill Management Options: Managing Machine Learning Skills in AI Center
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Cherry
2 months agoTamekia
2 months ago