Practice Free AIF-C01 Exam Online Questions
An AI practitioner has built a deep learning model to classify the types of materials in images. The AI practitioner 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)
A company has created a custom model by fine-tuning an existing large language model (LLM) from Amazon Bedrock. The company wants to deploy the model to production and use the model to handle a steady rate of requests each minute.
Which solution meets these requirements MOST cost-effectively?
- A . Deploy the model by using an Amazon EC2 compute optimized instance.
- B . Use the model with on-demand throughput on Amazon Bedrock.
- C . Store the model in Amazon S3 and host the model by using AWS Lambda.
- D . Purchase Provisioned Throughput for the model on Amazon Bedrock.
A company trains image and text generation models on Amazon SageMaker AI. The company releases the models by using Amazon Bedrock. The company must retain a tamper-proof, queryable record of every API call from SageMaker AI, Amazon Bedrock, and AWS Identity and Access Management (IAM).
Which AWS service will meet these requirements?
- A . AWS Trusted Advisor
- B . Amazon Macie
- C . AWS CloudTrail Lake
- D . Amazon Inspector
A company is implementing intelligent agents to provide conversational search experiences for its customers. The company needs a database service that will support storage and queries of embeddings from a generative AI model as vectors in the database.
Which AWS service will meet these requirements?
- A . Amazon Athena
- B . Amazon Aurora PostgreSQL
- C . Amazon Redshift
- D . Amazon EMR
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
A healthcare company wants to create a model to improve disease diagnostics by analyzing patient voices. The company has recorded hundreds of patient voices for this project. The company is currently filtering voice recordings according to duration and language.
- A . Data collection
- B . Data preprocessing
- C . Feature engineering
- D . Model training
A company deployed AI agents to automate manual decision-making processes.
Which metric measures the immediate value of this deployment?
- A . Size of the network effect
- B . Reduction of the cost for each decision
- C . Additional revenue from market expansion
- D . Potential value of additional vertical solutions
A company is introducing a new feature for its application. The feature will refine the style of output messages. The company will fine-tune a large language model (LLM) on Amazon Bedrock to implement the feature.
Which type of data does the company need to meet these requirements?
- A . Samples of only input messages
- B . Samples of only output messages
- C . Samples of pairs of input and output messages
- D . Separate samples of input and output messages
A real estate company is developing an ML model to predict house prices by using sales and marketing data. The company wants to use feature engineering to build a model that makes accurate predictions.
Which approach will meet these requirements?
- A . Understand patterns by providing data visualization.
- B . Tune the model’s hyperparameters.
- C . Create or select relevant features for model training.
- D . Collect data from multiple sources.
A company wants to keep its foundation model (FM) relevant by using the most recent data. The company wants to implement a model training strategy that includes regular updates to the FM.
Which solution meets these requirements?
- A . Batch learning
- B . Continuous pre-training
- C . Static training
- D . Latent training