Amazon AIF-C01 Dumps
AWS Certified AI Practitioner- 65 Questions & Answers
- Update Date : September 02, 2024
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Amazon AIF-C01 Sample Questions
Question # 1A company is using few-shot prompting on a base model that is hosted on Amazon Bedrock. The model currently uses 10 examples in the prompt. The model is invoked once daily and is performing well. The company wants to lower the monthly cost. Which solution will meet these requirements?
A. Customize the model by using fine-tuning.
B. Decrease the number of tokens in the prompt.
C. Increase the number of tokens in the prompt.
D. Use Provisioned Throughput.
Question # 2
A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions. Which business objective should the company use to evaluate the effect of the LLM chatbot?
A. Website engagement rate
B. Average call duration
C. Corporate social responsibility
D. Regulatory compliance
Question # 3
A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy. Which additional data does the company need to meet these requirements?
A. Pairs of chatbot responses and correct user intents
B. Pairs of user messages and correct chatbot responses
C. Pairs of user messages and correct user intents
D. Pairs of user intents and correct chatbot responses
Question # 4
A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text. Which type of model meets this requirement?
A. Topic modeling
B. Clustering models
C. Prescriptive ML models
D. BERT-based models
Question # 5
An AI practitioner is building a model to generate images of humans in various professions. The AIpractitioner discovered that the input data is biased and that specific attributes affect the imagegeneration and create bias in the model.Which technique will solve the problem?
A. Data augmentation for imbalanced classes
B. Model monitoring for class distribution
C. Retrieval Augmented Generation (RAG)
D. Watermark detection for images
Question # 6
A company is building an ML model. The company collected new data and analyzed the data by creating a correlation matrix, calculating statistics, and visualizing the data. Which stage of the ML pipeline is the company currently in?
A. Data pre-processing
B. Feature engineering
C. Exploratory data analysis
D. Hyperparameter tuning
Question # 7
Which functionality does Amazon SageMaker Clarify provide?
A. Integrates a Retrieval Augmented Generation (RAG) workflow
B. Monitors the quality of ML models in production
C. Documents critical details about ML models
D. Identifies potential bias during data preparation
Question # 8
An AI practitioner has built a deep learning model to classify the types of materials in images. The AIpractitioner now wants to measure the model performance.Which metric will help the AI practitioner evaluate the performance of the model?
A. Confusion matrix
B. Correlation matrix
C. R2 score
D. Mean squared error (MSE)
Question # 9
A company wants to develop an educational game where users answer questions such as the following: "A jar contains six red, four green, and three yellow marbles. What is the probability of choosing a green marble from the jar?" Which solution meets these requirements with the LEAST operational overhead?
A. Use supervised learning to create a regression model that will predict probability.
B. Use reinforcement learning to train a model to return the probability.
C. Use code that will calculate probability by using simple rules and computations.
D. Use unsupervised learning to create a model that will estimate probability density.
Question # 10
A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources. Which solution will meet this requirement?
A. Use a different FM
B. Choose a lower temperature value
C. Create an Amazon Bedrock knowledge base
D. Enable model invocation logging
Question # 11
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis.The company wants to know how much information can fit into one prompt.Which consideration will inform the company's decision?
A. Temperature
B. Context window
C. Batch size
D. Model size
Question # 12
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company needs the LLM to produce more consistent responses to the same input prompt. Which adjustment to an inference parameter should the company make to meet these requirements?
A. Decrease the temperature value
B. Increase the temperature value
C. Decrease the length of output tokens
D. Increase the maximum generation length
Question # 13
A company wants to develop a large language model (LLM) application by using Amazon Bedrock andcustomer data that is uploaded to Amazon S3. The company's security policy states that each teamcan access data for only the team's own customers.Which solution will meet these requirements?
A. Create an Amazon Bedrock custom service role for each team that has access to only the team'scustomer data.
B. Create a custom service role that has Amazon S3 access. Ask teams to specify the customer nameon each Amazon Bedrock request.
C. Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customerdata.
D. Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each teamthat have access to only each team's customer folders.