Question: While writing Prompt for GenAI use case, you encounter a situation where the model consistently provides inaccurate responses. What should you do FIRST to address this issue?Instruction: Choose the option that best answers the questionIncrease the complexity of the prompts to challenge the model further.Modify the training data without analyzing the root cause of the inaccuracies.Review the existing prompts and refine them to provide clearer instructions.Ignore the inaccuracies as they might improve over time with more training.

Question: As a GenAI Delivery Practitioner you will be implementing GenAI use cases for your client. As part of this implementation, you will write or customize Prompts. Which of the following NOT right about Prompt?Instruction: Choose the option that best answers the questionA way to optimize Gen AI resultsA technique used in LLMs to guide or direct their output by providing them with a specific promptSet of instructions or data, where the goal is to improve the accuracy & relevance of the model's outputAlgorithm to execute specific Machine Learning tasks in the Technology DeliveryNone of the above

Writing accurate and precise prompts is crucial for getting desired responses from AI. Providing context helps AI understand user requirements better. Tailored prompts for specific use-cases save time and effort. AI can emulate different writing styles if specified. Practice and experimentation are key to writing effective prompts.

What should be avoided when designing a prompt for ChatGPT?Options: Pick one correct answer from belowIncluding irrelevant information and anecdotesUsing complex and technical languageProviding clear instructions and examplesAsking only yes/no questions in the prompt

Question: You are executing Real Time ‘Root Cause Analysis of Job failure’ use case leveraging Generative AI. There can be different root causes for different type of job failures. While writing Prompt we have to give example. Which of the following Prompt Engineering practice you will follow?Instruction: Choose the option that best answers the questionFew-Short LearningZero-Short LearningOne-Short LearningAmple-Short LearningNone of the above

You are solving a classification problem with a highly imbalanced class. The majority class is occurring 98% of times in the training data.Now when you come with predictions, your model has 98% accuracy on test data. Which of the following is true in such a case?1. Accuracy metric is not a good idea for imbalanced class problems.2. Accuracy metric is a good idea for imbalanced class problems.3. Precision and recall metrics are good for imbalanced class problems.4. Precision and recall metrics aren’t good for imbalanced class problems.