Module 2: Prompt Engineering: Techniques and Approaches
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In this post, I provide accurate answers and detailed explanations for Module 2: Prompt Engineering: Techniques and Approaches of Course 3: Generative AI: Prompt Engineering Basics – IBM Generative AI Engineering Professional Certificate
Whether you’re preparing for quizzes or brushing up on your knowledge, these insights will help you master the concepts effectively. Let’s dive into the correct answers and detailed explanations for each question.
Practice Quiz: Writing Effective Prompts
Practice Assignment
1. Which of the following techniques helps text prompts guide LLMs to generate responses within specific boundaries, ensuring that the output aligns with the desired requirements?
- Bias mitigation
- Framing ✅
- Task specification
- Domain expertise
Explanation:
Framing helps text prompts guide large language models (LLMs) to generate responses within specific boundaries, ensuring that the output aligns with the desired requirements. By setting the right context and constraints in the prompt, you can guide the AI to produce more focused and relevant responses.
2. Which of the following prompt engineering approaches involves breaking down complex tasks into easier ones through a sequence of simpler prompts to guide the model toward the intended outcome?
- Chain-of-Thought ✅
- Tree-of-Thoughts
- Interview pattern
- Cognitive building
Explanation:
Chain-of-Thought involves breaking down complex tasks into simpler, more manageable ones through a series of prompts. This technique helps guide the model step-by-step toward the desired outcome by focusing on incremental, logical steps.
3. How does the interview pattern approach enhance the interaction with generative AI models?
- By providing a single static prompt to the model.
- By promoting a back-and-forth exchange of information with the model. ✅
- By focusing on a conventional prompting approach
- By hierarchically structuring a prompt or query
Explanation:
The Interview pattern approach enhances the interaction with generative AI models by promoting a back-and-forth exchange of information. This approach mimics an interview-style dialogue, which allows for clarification and refinement of responses.
Graded Quiz: Prompt Engineering: Techniques and Approaches
Graded Assignment
4. Imagine you are planning a business trip, and you want to use the interview pattern approach to prompt an AI model to assist you in planning your itinerary. What would be the benefit of this approach in comparison to a traditional static prompt?
- The model will minimize the need for any user interaction
- The model will provide a single predetermined itinerary
- The model will ask for your preferences and adjust the itinerary accordingly ✅
- The model will generate a random travel plan.
Explanation:
The interview pattern uses a back-and-forth exchange to adapt the output to your preferences, unlike a static prompt that gives a fixed result.
5. Jennifer wants to request some useful information about a complex medical condition using a large language model. Which among the following techniques should she employ on the text prompt to ensure that the generated content is relevant, accurate, and precise for this specialized field?
- Task specification
- Bias mitigation
- Domain expertise ✅
- Framing
Explanation:
For specialized topics like medical conditions, domain expertise ensures the AI uses the correct terminology and provides accurate, relevant responses.
6. Imagine you are a content developer working with LLMs, and you must ensure that the responses generated are indiscriminatory and neutral. Which among the following techniques would you employ with your text prompts to instruct the model appropriately?
- Contextual guidance
- Bias mitigation ✅
- Zero-shot prompting
- Few-shot prompting
Explanation:
Bias mitigation helps reduce discrimination in AI responses, ensuring fairness and neutrality.
7. Imagine you are using the Chain-of-Thought approach to teach a generative AI model how to solve a mathematical problem. What is the key component of a prompt in this approach?
- A prompt includes a list of formulae to solve the question.
- A prompt consists of a question and a correct answer for context. ✅
- A prompt includes a series of related questions without the correct answer.
- A prompt includes only a question without an answer.
Explanation:
In the Chain-of-Thought approach, the model is guided through a series of reasoning steps. Providing both a question and a correct answer helps the AI understand the reasoning process, so it can replicate that approach for other similar tasks. This method improves the model’s ability to solve complex problems step by step by mimicking the provided reasoning.
Related contents:
Module 1: Prompt Engineering for Generative AI
Module 3: Course Quiz, Project, and Wrap-up