UiPath-SAIv1 Exam Topics
UiPath-SAIv1 Exam Overview :
| Exam Name: | UiPath Certified Professional Specialized AI Professional v1.0 |
| Exam Code: | UiPath-SAIv1 |
| Certifications: | UiPath Certified Professional Specialized AI Professional Certification |
| See Expected Questions: | UiPath UiPath-SAIv1 Expected Questions in Actual Exam |
UiPath-SAIv1 Exam Objectives :
| Section | Objectives |
|---|---|
| UiPath Document Understanding Framework | This topic covers the implementation of UiPaths Document Understanding Framework, which includes building Proof-of-Concept (POC) models and automation components. Students will learn to utilize the Document Understanding Process template to design robust automation solutions. |
| UiPath Studio - Document Understanding Activities | Under this topic, students will explore the Document Object Model and its significance in Document Understanding. They will be guided on choosing the right OCR engine and selecting the most suitable classifiers/extractors for their projects. Additionally, they will learn to configure human validation steps, train classifiers for improved performance, and evaluate their models. |
| Document Understanding Specific UiPath Implementation Methodology | This section focuses on the data analysis and collection aspects of document understanding. Students will learn to gather and analyze data regarding document types, extracted fields, and language considerations. |
| UiPath AI Center | The UiPath AI Center topic introduces students to the world of AI, ML, NLP, DL, and Computer Vision. It explains the differences between various machine learning techniques and describes the functionality and user personas of UiPath AI Center. Students will learn about the types of ML models, deployment methods, and out-of-the-box applications. |
| UiPath Communications Mining - Model Training | Here, students will delve into the golden rules of label and general fields training in UiPath Communications Mining. They will understand the importance of the Train tab and generative annotation and extraction techniques. The sub-topics will provide a comprehensive understanding of configuring extractions, generating suggestions, and improving extraction performance. |
| UiPath Communications Mining – Taxonomy Design | This section focuses on the design aspect of UiPath Communications Mining. Students will learn to create effective label taxonomy structures, differentiate between analytics and automation taxonomies, and understand the different types of general fields. The sub-topics will provide examples and best practices to ensure a well-designed taxonomy for their projects. |
| UiPath Communications Mining – Setup | Under this topic, students will explore the three main components of data in UiPath Communications Mining: data sources, datasets, and projects. They will learn to manage and configure general fields, import taxonomies, and understand the distinction between tone analysis and label sentiment. The sub-topics ensure a smooth setup process for effective model training and deployment. |
| UiPath Communications Mining – Discover | This section focuses on the Discover phase of UiPath Communications Mining. Students will learn about label clusters, the Search functionality, and the risks associated with its excessive use. The sub-topics will provide best practices and guidelines to ensure effective model training. |
| UiPath Communications Mining – Explore | Here, students will understand the Explore phase, where they will learn about label and entity predictions and their significance. They will differentiate between label predictions and suggestions and understand the importance of Shuffle, Teach Label, and Low Confidence in model training. The sub-topics will provide insights into making informed decisions during the Explore phase. |
| UiPath Communications Mining - Refine and Maintain | This section focuses on the refinement and maintenance of models in UiPath Communications Mining. Students will learn about the importance of the Refine phase, precision and recall metrics, and the Model Rating system. They will analyze various aspects, such as label performance, dataset coverage, and balance, and suggest improvements. The sub-topics will also cover addressing bias, managing model performance erosion, and maintaining models in production. |
| Analytics & Monitoring | This topic covers the analytical capabilities offered by UiPath Communications Mining. Students will learn to create customized dashboards, analyze label and verbatim volumes, sentiment trends, and conversation characteristics. The sub-topics, such as Reports, Label Summary, Trends, and Alert Center, provide a comprehensive understanding of monitoring and analyzing data effectively. |
| Automation and Model Management | Here, students will explore the application of CI/CD best practices for model management. They will learn about stream management, threshold selection, and pinning model versions for production and staging. The sub-topics, including the Dispatcher Framework and Communications Mining Studio Activities, provide a practical understanding of automation and model deployment. |
| Updates introduced to 2023.10 | This section highlights the latest updates in UiPaths 2023.10 release. Students will learn about enhancements to the Document Manager, Taxonomy Manager, and the introduction of Document Understanding Cloud APIs. They will also explore new features, such as the deprecation of certain components, improved field configuration, and cross-platform classification validation. |
Updates in the UiPath-SAIv1 Exam Topics:
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