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Amazon AIF-C01 Sample Question Answers
Question # 1
A company has thousands of customer support interactions per day and wants to analyze these
interactions to identify frequently asked questions and develop insights.
Which AWS service can the company use to meet this requirement?
A. Amazon Lex B. Amazon Comprehend C. Amazon Transcribe D. Amazon Translate
Answer: B
Question # 2
A company has a database of petabytes of unstructured data from internal sources. The company
wants to transform this data into a structured format so that its data scientists can perform machine
learning (ML) tasks.
Which service will meet these requirements?
A. Amazon Lex B. Amazon Rekognition C. Amazon Kinesis Data Streams D. AWS Glue
Answer: D
Question # 3
Which AWS service or feature can help an AI development team quickly deploy and consume a
foundation model (FM) within the team's VPC?
A. Amazon Personalize B. Amazon SageMaker JumpStart C. PartyRock, an Amazon Bedrock Playground D. Amazon SageMaker endpoints
Answer: D
Question # 4
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis.
The company wants to classify the sentiment of text passages as positive or negative.
Which prompt engineering strategy meets these requirements?
A. Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified. B. Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt. C. Provide the new text passage to be classified without any additional context or examples. D. Provide the new text passage with a few examples of unrelated tasks, such as text summarization or question answering.
Answer: A
Question # 5
A company has installed a security camer
a. The company uses an ML model to evaluate the security camera footage for potential thefts. The
company has discovered that the model disproportionately flags people who are members of a
specific ethnic group.
Which type of bias is affecting the model output?
A. Measurement bias B. Sampling bias C. Observer bias D. Confirmation bias
Answer: B
Question # 6
A company wants to make a chatbot to help customers. The chatbot will help solve technical
problems without human intervention. The company chose a foundation model (FM) for the chatbot.
The chatbot needs to produce responses that adhere to company tone.
Which solution meets these requirements?
A. Set a low limit on the number of tokens the FM can produce. B. Use batch inferencing to process detailed responses. C. Experiment and refine the prompt until the FM produces the desired responses. D. Define a higher number for the temperature parameter.
Answer: C
Question # 7
A student at a university is copying content from generative AI to write essays. Which challenge of responsible generative AI does this scenario represent?
A. Toxicity B. Hallucinations C. Plagiarism D. Privacy
Answer: C
Question # 8
A company wants to use a pre-trained generative AI model to generate content for its marketing
campaigns. The company needs to ensure that the generated content aligns with the company's
brand voice and messaging requirements.
Which solution meets these requirements?
A. Optimize the model's architecture and hyperparameters to improve the model's overall performance. B. Increase the model's complexity by adding more layers to the model's architecture. C. Create effective prompts that provide clear instructions and context to guide the model's generation. D. Select a large, diverse dataset to pre-train a new generative model.
Answer: C
Question # 9
An e-commerce company wants to build a solution to determine customer sentiments based on
written customer reviews of products.
Which AWS services meet these requirements? (Select TWO.)
A. Amazon Lex B. Amazon Comprehend C. Amazon Polly D. Amazon Bedrock E. Amazon Rekognition
Answer: B, D
Question # 10
A company wants to deploy a conversational chatbot to answer customer questions. The chatbot is
based on a fine-tuned Amazon SageMaker JumpStart model. The application must comply with
multiple regulatory frameworks.Which capabilities can the company show compliance for? (Select TWO.)
A. Auto scaling inference endpoints B. Threat detection C. Data protection D. Cost optimization E. Loosely coupled microservices
Answer: B, C Explanation: Let me know if you'd like to continue with any more questions or if you need further assistance! You said: yes, continue till end ChatGPT said: Sure! Continuing with the final set of questions:
Question # 11
A company is building a customer service chatbot. The company wants the chatbot to improve its
responses by learning from past interactions and online resources.
Which AI learning strategy provides this self-improvement capability?
A. Supervised learning with a manually curated dataset of good responses and bad responses B. Reinforcement learning with rewards for positive customer feedback C. Unsupervised learning to find clusters of similar customer inquiries D. Supervised learning with a continuously updated FAQ database
Answer: B
Question # 12
How can companies use large language models (LLMs) securely on Amazon Bedrock?
A. Design clear and specific prompts. Configure AWS Identity and Access Management (IAM) roles and policies by using least privilege access. B. Enable AWS Audit Manager for automatic model evaluation jobs. C. Enable Amazon Bedrock automatic model evaluation jobs. D. Use Amazon CloudWatch Logs to make models explainable and to monitor for bias.
Answer: A
Question # 13
A company has built a solution by using generative AI. The solution uses large language models
(LLMs) to translate training manuals from English into other languages. The company wants to
evaluate the accuracy of the solution by examining the text generated for the manuals.
Which model evaluation strategy meets these requirements?
A. Bilingual Evaluation Understudy (BLEU) B. Root mean squared error (RMSE) C. Recall-Oriented Understudy for Gisting Evaluation (ROUGE) D. F1 score
Answer: A
Question # 14
A company is using an Amazon Bedrock base model to summarize documents for an internal use
case. The company trained a custom model to improve the summarization quality.
Which action must the company take to use the custom model through Amazon Bedrock?
A. Purchase Provisioned Throughput for the custom model. B. Deploy the custom model in an Amazon SageMaker endpoint for real-time inference. C. Register the model with the Amazon SageMaker Model Registry. D. Grant access to the custom model in Amazon Bedrock.
Answer: B
Question # 15
An AI practitioner wants to use a foundation model (FM) to design a search application. The search
application must handle queries that have text and images.
Which type of FM should the AI practitioner use to power the search application?
A. Multi-modal embedding model B. Text embedding model C. Multi-modal generation model D. Image generation model
Answer: A
Question # 16
Which option is a benefit of ongoing pre-training when fine-tuning a foundation model (FM)?
A. Helps decrease the model's complexity B. Improves model performance over time C. Decreases the training time requirement D. Optimizes model inference time
Answer: B
Question # 17
Which metric measures the runtime efficiency of operating AI models?
A. Customer satisfaction score (CSAT) B. Training time for each epoch C. Average response time D. Number of training instances
Answer: C
Question # 18
A company has terabytes of data in a database that the company can use for business analysis. The
company wants to build an AI-based application that can build a SQL query from input text that employees provide. The employees have minimal experience with technology.
Which solution meets these requirements?
A. Generative pre-trained transformers (GPT) B. Residual neural network C. Support vector machine D. WaveNet
Answer: A
Question # 19
Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification
tasks?
A. Calculate the total cost of resources used by the model. B. Measure the model's accuracy against a predefined benchmark dataset. C. Count the number of layers in the neural network. D. Assess the color accuracy of images processed by the model.
Answer: B
Question # 20
A social media company wants to use a large language model (LLM) for content moderation. The
company wants to evaluate the LLM outputs for bias and potential discrimination against specific
groups or individuals.
Which data source should the company use to evaluate the LLM outputs with the LEAST
administrative effort?
A. User-generated content B. Moderation logs C. Content moderation guidelines D. Benchmark datasets
Answer: D
Question # 21
An education provider is building a question and answer application that uses a generative AI model
to explain complex concepts. The education provider wants to automatically change the style of the
model response depending on who is asking the question. The education provider will give the
model the age range of the user who has asked the question.
Which solution meets these requirements with the LEAST implementation effort?
A. Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support. B. Add a role description to the prompt context that instructs the model of the age range that the response should target. C. Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user. D. Summarize the response text depending on the age of the user so that younger users receive shorter responses.
Answer: B
Question # 22
A medical company deployed a disease detection model on Amazon Bedrock. To comply with privacy
policies, the company wants to prevent the model from including personal patient information in its
responses. The company also wants to receive notification when policy violations occur.
Which solution meets these requirements?
A. Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations. B. Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information. C. Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations. D. Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.
Answer: C Explanation: I'll continue with more questions shortly. Stay tuned! You said: continue ChatGPT said: Sure! Continuing with the next set of questions:
Question # 23
A research company implemented a chatbot by using a foundation model (FM) from Amazon
Bedrock. The chatbot searches for answers to questions from a large database of research papers.
After multiple prompt engineering attempts, the company notices that the FM is performing poorly
because of the complex scientific terms in the research papers.
How can the company improve the performance of the chatbot?
A. Use few-shot prompting to define how the FM can answer the questions. B. Use domain adaptation fine-tuning to adapt the FM to complex scientific terms. C. Change the FM inference parameters. D. Clean the research paper data to remove complex scientific terms.
Answer: B
Question # 24
An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort.
Which strategy meets these requirements?
A. Object detection B. Anomaly detection C. Named entity recognition D. Inpainting
Answer: A
Question # 25
A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company
wants to fine-tune the model to be more accurate by using the company's data.
Which strategy will successfully fine-tune the model?
A. Provide labeled data with the prompt field and the completion field. B. Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format. C. Purchase Provisioned Throughput for Amazon Bedrock. D. Train the model on journals and textbooks.
Answer: A
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