UiPath Certified Professional Specialized AI Professional v1.0 - UiPath-SAIv1 Exam Practice Test

A. Import, Classification, Text Extractor, and Data Validation

B. Load Taxonomy, Digitization, Categorization, Data Validation, and Export

C. Load Document, Categorization, Data Extraction, and Validation

D. Load Taxonomy, Digitization, Classification, Data Extraction, and Data Validation Export

A. Using a C/C++ IDE (Integrated Development Environment), then upload the code to Al Center IDE.

B. Using the Al Center IDE (Integrated Development Environment).

C. Using a Python IDE (Integrated Development Environment) or an AutoML platform.

D. Using the Al Center model builder.

A. Manual and model-based data extraction.

B. Rule-based and hybrid data extraction.

C. Hybrid and manual data extraction.

D. Rule-based and model-based data extraction.

A. The trained-from-scratch general fields depend on the model version, while the ones that are pre-trained do not.

B. The trained-from-scratch general fields are entirely user-trained, while the ones that are pre-trained are typically based on a set of standard or custom-defined rule

C. The trained-from-scratch general fields need to be normalized to be used in downstream automation, while the ones that are pre-trained can only be used in dashboards within the platform.

D. The trained-from-scratch general fields have better accuracy, while the pre-trained general fields have a longer training time.

A. Use the "Low confidence" training mode to pin the label to more communications.

B. Use the 'Teach" training mode to pin the label to more communications.

C. Use the "Rebalance" training mode to pin the label to more communications.

D. Use the "Search" feature to pin the label to more communications.

A. Pre-trained. custom training, and fine-tunable.

B. Pre-trained, custom training, and reviewed.

C. Custom training, fine-tunable, and reviewed.

D. Pre-trained. fine-tunable, and reviewed.

A. The position on the page.

B. The extraction confidence and the digitization confidence.

C. The page number from which the field was extracted and the exact position on the page.

D. The number of occurrences and the extraction confidence.

A. UiPath RPA and AI Center have overlapping functionalities, so they are not designed to work together in process improvement. Each tool serves different purposes and is used independently to achieve automation and AI capabilities, respectively.

B. UiPath RPA and AI Center work together in process improvement by utilizing RPA bots to execute models deployed in Action Center that can be monitored in Insights. The ML models process data and generate insights, which are then used by the RPA bots to make informed decisions and carry out automated actions.

C. UiPath RPA and AI Center are independent tools that do not work together in process improvement.
RPA focuses on task automation, while AI Center is primarily used for training and deploying machine learning models.

D. UiPath RPA and AI Center work together in process improvement by leveraging RPA capabilities to automate repetitive tasks and integrating AI Center to enhance decision-making and cognitive abilities.RPA bots can collect data, perform actions, and feed information to ML models in AI Center, which in turn can analyze the data and make predictions.

A. Variables Panel

B. Activities Panel

C. Manage Packages

D. Outline Panel