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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:

1. How do the prediction mechanisms for labels and general fields differ in the UiPath Communications Mining platform?

A) Labels and general fields are both predicted based on the text of the message, with no consideration given to metadata properties or contextual surrounding text.
B) Label predictions rely solely on metadata properties, general fields are learnt from the presence of certain key phrases in the text.
C) Label predictions are made based on the text of the message as well as some metadata properties, while general fields are learnt from the assigned span of text and the context of the text surrounding that span.
D) Labels predictions are based on assigned span of text and entities are predicted solely from metadata properties.

2. What is the default visibility of an ML skill?

A) An ML skill is by default private and can be made public.
B) An ML skill is by default private and can't be made public.
C) An ML skill is by default public and can be made private.
D) An ML skill is by default public and can't be made private.

3. Having the taxonomy in a file, shared and updated across multiple projects, what is the most convenient way to load it in a UiPath Studio project?

A) Using Load Taxonomy activity.
B) Using DeserializeTaxonomy activity.
C) Using DocumentTaxonomy.Deserialize method inside an Assign activity.
D) Using Read Taxonomy activity.

4. What is the primary advantage of the One Click Extraction feature in UiPath's Document Understanding interface?

A) It automates the creation of document extractors by automatically creating Datasets, Pipelines, and ML Skills but requires manual creation of Pipelines.
B) It allows training document extractors without manually creating Datasets and Pipelines, but you need to manually deploy the ML Skills in AI Center.
C) It provides a simplified way to manually create Datasets, Pipelines, and Datasets for document extraction.
D) It allows training document extractors without manually creating Datasets, Pipelines, and ML Skills in AI Center.

5. What information is required when creating a data labeling session?

A) Data labeling name, language, and number of documents.
B) Data labeling session name and dataset.
C) Data labeling name, dataset. and Al Center project.
D) Dataset and Al Center project.

Solutions: