NCP-GENL Prompt Engineering Practice Test 1 — 15 Questions

Question 1

A developer is building a technical support bot that must analyze complex log files to identify root causes. The initial zero-shot prompt often yields generic summaries that miss specific error codes. Which strategy should the developer implement to ensure the model performs logical deduction step-by-step before providing a final answer?

Choose an answer to begin — your selection is scored in the full session.

Answer

Temperature reduction to zero

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Chain-of-Thought (CoT) prompting

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Increasing the frequency penalty

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Few-shot prompting with summaries

Question 2

When designing a prompt for a high-stakes financial application, which TWO techniques are most effective for mitigating the risk of prompt injection and ensuring the model adheres to its system-defined guardrails?

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Using distinct delimiters for user input

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Implementing recursive character splitting

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Placing user input before the system instructions

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Utilizing a robust system-level prompt

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Applying a high Top-p value

Question 3

An AI practitioner wants to generate a list of creative marketing slogans for a new product but finds the output too repetitive and predictable. Which hyperparameter should be adjusted to increase the randomness and diversity of the slogans generated by the prompt?

Answer

Presence penalty

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Temperature

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Max tokens

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Stop sequences

Question 4

A data scientist is using few-shot prompting to classify customer feedback into five distinct categories. Which THREE factors are most critical for selecting effective examples to include in the prompt?

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Label distribution balance

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Example diversity and coverage

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Semantic similarity to the target input

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Alphabetical ordering of examples

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Total character count of all examples

Question 5

Which prompting technique involves the model generating multiple different reasoning paths and then selecting the most common answer among them to improve the accuracy of complex math problems?

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Least-to-most prompting

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Self-consistency prompting

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Tree-of-Thought prompting

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ReAct prompting

Question 6

A developer wants to implement a 'Persona' or 'Role-playing' prompt to improve a customer service bot. Which TWO benefits does this technique provide for the model's output?

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Consistent tone and stylistic alignment

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Reduction in total inference latency

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Implicit context for domain-specific jargon

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Elimination of the need for stop sequences

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Automatic verification of factual accuracy

Question 7

Which component of a prompt is primarily responsible for providing the model with the specific information it needs to answer a query, such as a retrieved document or a set of database records?

Answer

The Instruction

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The Context

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The Output Indicator

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The Few-shot Examples

Question 8

When utilizing the ReAct (Reason + Act) prompting framework, what is the primary purpose of the 'Observation' step in the model's iterative loop?

Answer

It generates the final answer for the user

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It provides the model with the result of an action

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It defines the persona for the reasoning trace

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It is used to penalize repetitive reasoning paths

Question 9

An engineer is struggling with 'hallucinations' in a model that summarizes legal documents. Which TWO prompt engineering adjustments are most likely to reduce the occurrence of fabricated information?

Answer

Instructing the model to say 'I don't know' if unsure

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Adding a requirement for direct quotes and citations

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Increasing the Top-k parameter to 100

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Removing all few-shot examples from the prompt

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Using a very high temperature setting

Question 10

Which prompting strategy is specifically designed to solve problems by first asking the model to break down a complex task into smaller, manageable sub-problems and then solving each one in order?

Answer

Chain-of-Thought prompting

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Least-to-most prompting

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Zero-shot prompting

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Negative prompting

Question 11

A developer is using an LLM to generate SQL queries from natural language. The model frequently confuses table names and column relationships. Which prompt engineering technique would most effectively ground the model's output in the specific database schema being used?

Answer

Increasing the max token limit

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Adding a 'think step-by-step' instruction

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Including the DDL (Data Definition Language) in the context

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Using a more creative persona for the model

Question 12

Which TWO of the following are primary reasons for using delimiters (such as ### or ---) in a prompt that includes both instructions and a long source document?

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To help the model distinguish between instructions and data

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To reduce the total number of tokens used in the prompt

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To prevent the model from following commands inside the data

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To bypass the model's safety and content filters

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To automatically translate the prompt into multiple languages

Question 13

A user wants an LLM to rewrite a paragraph in a 'professional and concise' style. The model provides a professional version, but it is still quite long. Which change to the prompt is most likely to achieve the desired result?

Answer

Changing the temperature to 1.0

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Using a negative prompt like 'Do not use many words'

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Providing a few-shot example of a concise rewrite

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Repeating the word 'concise' five times in the prompt

Question 14

Which TWO of the following strategies effectively reduce hallucination in RAG-based NVIDIA NeMo applications? (Select exactly TWO)

Accepted Answer

Require the model to cite the specific document ID for every claim.. Reducing hallucinations in Retrieval-Augmented Generation requires a two-pronged approach: restricting the model to the provided context and encouraging the model to acknowledge limitations. By explicitly instructing the model to rely only on provided documents and allowing for an 'I don't know' response, the reliability of the system increases. These techniques are standard best practices for maintaining high accuracy in enterprise-grade NVIDIA AI deployments.

Answer

Instruct the model to ignore context if it already knows the answer.

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Set the sampling temperature to 1.5 to maximize creativity.

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Increase the number of context documents to over 100 for every query.

Question 15

When designing prompts for NVIDIA NeMo Guardrails, which THREE of the following are best practices to ensure alignment and safety? (Select exactly THREE)

Accepted Answer

Define clear negative constraints for off-topic interactions.. NeMo Guardrails work best when instructions are explicit, negative constraints are clearly defined, and topic boundaries are strictly enforced. By defining what the model should not do, providing clear examples of off-topic queries, and maintaining consistent persona instructions, developers can create a robust safety layer. These practices ensure the model stays within the intended operational domain while providing consistent and helpful assistance.

Answer

Use highly complex, ambiguous language to test robustness.

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Encourage the model to ignore user input if it sounds frustrated.