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UiPath Certified Professional Agentic Automation Associate (UiAAA) Sample Questions:

1. What steps must be completed when creating evaluations from scratch for a new evaluation set in UiPath?

A) Assign evaluators immediately after creating the new evaluation set name, then configure inputs and expected outputs later.
B) Once the evaluation set is created, all included evaluations are automatically scored based only on input values and expected outputs.
C) The evaluation set can only be created using imported JSON data from previous evaluations of other agents.
D) Add a name to the evaluation set, provide input values and expected output, save each evaluation, and assign evaluators before running the evaluation set.

2. When creating an Action app, what is the purpose of defining the "Approve" and "Deny" outcomes within the Action schema?

A) To dynamically update user-facing form labels with the action result.
B) To guide the agent's next steps based on the review results of Input/Output properties.
C) To save user input as mandatory action schema properties during automation execution.
D) To ensure the app validates search results and prevents faulty submissions.

3. A developer is working on fine-tuning an LLM for generating step-by-step automation guides. After providing a detailed example prompt, they notice inconsistencies in the way the LLM interprets certain technical terms. What could be the reason for this behavior?

A) The LLM does not rely on tokenization for understanding prompts; instead, misinterpretation arises from inadequate pre-programmed definitions of technical terms.
B) The LLM's tokenization process may have split complex technical terms into multiple tokens, causing slight variations in how the model interprets and weights their relationships within the context of the prompt.
C) The inconsistency is related to the token limit defined for the prompt's length, which affects the LLM's ability to complete a response rather than its understanding of technical terms.
D) The LLM's interpretation is solely based on the frequency of terms within the training dataset, rendering technical nuances irrelevant during generation.

4. An agent uses Web Search, Slack integration, and a custom process to resolve IT support tickets. The agent must:
* Retrieve relevant troubleshooting steps from the web.
* Notify the user via Slack if a solution is found.
* Escalate unresolved tickets via a custom process.
Which evaluation strategy ensures comprehensive coverage while avoiding redundancy?

A) Create 30 evaluations for Slack notifications, 30 for web searches, and 30 for escalation processes.
B) Group evaluations into sets: Valid web results triggering Slack notifications, Invalid web results triggering escalations, Edge cases.
C) Create more than 30 evaluations for Slack notifications, more than 30 for web searches, and more than
30 for escalation processes.
D) Use random input sampling across all tools and rely on the default "LLM-as-a-Judge" assertion.

5. Why would you choose the Argument input method for an activity field?

A) Prompts a person to supply the value each time the field is evaluated at runtime.
B) Applies one constant value you enter during design every time the agent executes the activity.
C) Lets the agent infer the field value at runtime using the Description and its reasoning.
D) Receives a runtime value from an agent input argument defined earlier in the workflow.

Solutions: