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UiPath UiPath-AAAv1 Exam Syllabus Topics:

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

1. A team is building an AI agent that drafts personalized marketing emails. The quality of the drafts depends on tone, alignment with brand voice, and personalization. What evaluation approach is best?

A) Random sampling with A/B testing.
B) Model-graded evaluation to capture nuanced style and relevance.
C) Deterministic evaluation using a checklist of key phrases.
D) Evaluation using a character count threshold to assess message quality.

2. In which scenario is a deterministic evaluation more appropriate than a model-graded one?

A) When evaluating the tone and helpfulness of agent responses.
B) When open-ended reasoning needs to be scored.
C) When the response quality depends on user satisfaction.
D) When the correct output is known and fixed.

3. How does the impact and feasibility matrix assist in prioritizing agentic automation use cases?

A) By identifying all feasible use cases without considering the potential impact or business benefit of implementing them.
B) By focusing solely on high-impact use cases without considering whether implementing them is feasible with available resources.
C) By evaluating use cases based on their potential business improvement and ease of implementation considering current resources and technology.
D) By prioritizing the automation of all processes regardless of their feasibility or actual impact on the organization.

4. 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 LLM's interpretation is solely based on the frequency of terms within the training dataset, rendering technical nuances irrelevant during generation.
D) 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.

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

Solutions: