AWS AIF-C01 Dumps (V12.02) Are Available to Boost Your Chances for Passing AWS Certified AI Practitioner Exam – Test 55 Demo Questions Online to Verify the Quality

1. An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data.

How should the AI practitioner prevent responses based on confidential data?

2. Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

A. Integration with Amazon S3 for object storage

B. Support for geospatial indexing and queries

C. Scalable index management and nearest neighbor search capability

D. Ability to perform real-time analysis on streaming data

3. A company wants to display the total sales for its top-selling products across various retail locations in the past 12 months.

Which AWS solution should the company use to automate the generation of graphs?

A. Amazon Q in Amazon EC2

B. Amazon Q Developer

C. Amazon Q in Amazon QuickSight

D. Amazon Q in AWS Chatbot

4. A company wants to build an interactive application for children that generates new stories based on classic stories. The company wants to use Amazon Bedrock and needs to ensure that the results and topics are appropriate for children.

Which AWS service or feature will meet these requirements?

5. A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model.

The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.

Which solution will meet these requirements?

6. A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company's products.

Which methodology should the company use to meet these requirements?

A. Supervised learning

B. Unsupervised learning

C. Reinforcement learning

D. Reinforcement learning from human feedback (RLHF)

7. A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts.

An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders.

What should the AI practitioner include in the report to meet the transparency and explainability requirements?

8. Which option is a use case for generative AI models?

9. An AI practitioner is using a large language model (LLM) to create content for marketing campaigns.

The generated content sounds plausible and factual but is incorrect.

Which problem is the LLM having?

10. A loan company is building a generative AI-based solution to offer new applicants discounts based on specific business criteria. The company wants to build and use an AI model responsibly to minimize bias that could negatively affect some customers.

Which actions should the company take to meet these requirements? (Select TWO.)

11. A medical company is customizing a foundation model (FM) for diagnostic purposes. The company needs the model to be transparent and explainable to meet regulatory requirements.

Which solution will meet these requirements?

A. Configure the security and compliance by using Amazon Inspector.

B. Generate simple metrics, reports, and examples by using Amazon SageMaker Clarify.

C. Encrypt and secure training data by using Amazon Macie.

D. Gather more data. Use Amazon Rekognition to add custom labels to the data.

12. A company is building a solution to generate images for protective eyewear. The solution must have high accuracy and must minimize the risk of incorrect annotations.

Which solution will meet these requirements?

13. A security company is using Amazon Bedrock to run foundation models (FMs). The company wants to ensure that only authorized users invoke the models. The company needs to identify any unauthorized access attempts to set appropriate AWS Identity and Access Management (IAM) policies and roles for future iterations of the FMs.

Which AWS service should the company use to identify unauthorized users that are trying to access Amazon Bedrock?

A. AWS Audit Manager

B. AWS CloudTrail

C. Amazon Fraud Detector

D. AWS Trusted Advisor

14. A company manually reviews all submitted resumes in PDF format. As the company grows, the company expects the volume of resumes to exceed the company's review capacity. The company needs an automated system to convert the PDF resumes into plain text format for additional processing.

Which AWS service meets this requirement?

15. A company wants to use large language models (LLMs) with Amazon Bedrock to develop a chat interface for the company's product manuals. The manuals are stored as PDF files.

Which solution meets these requirements MOST cost-effectively?

16. Which term describes the numerical representations of real-world objects and concepts that AI and natural language processing (NLP) models use to improve understanding of textual information?

17. A company is building an application that needs to generate synthetic data that is based on existing data.

Which type of model can the company use to meet this requirement?

18. A company wants to use generative AI to increase developer productivity and software development.

The company wants to use Amazon Q Developer.

What can Amazon Q Developer do to help the company meet these requirements?

19. A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment.

Which Amazon Bedrock pricing model meets these requirements?

20. A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model. The company needs to perform analysis on internal data and external data.

Which solution will meet these requirements?

21. What are tokens in the context of generative AI models?

22. An AI practitioner is using an Amazon Bedrock base model to summarize session chats from the customer service department. The AI practitioner wants to store invocation logs to monitor model input and output data.

Which strategy should the AI practitioner use?

23. A company needs to build its own large language model (LLM) based on only the company's private data. The company is concerned about the environmental effect of the training process.

Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?

24. A financial institution is using Amazon Bedrock to develop an AI application. The application is hosted in a VPC. To meet regulatory compliance standards, the VPC is not allowed access to any internet traffic.

Which AWS service or feature will meet these requirements?

25. A company built a deep learning model for object detection and deployed the model to production.

Which AI process occurs when the model analyzes a new image to identify objects?

A. Training

B. Inference

C. Model deployment

D. Bias correction

26. A company is using Amazon SageMaker Studio notebooks to build and train ML models. The company stores the data in an Amazon S3 bucket. The company needs to manage the flow of data from Amazon S3 to SageMaker Studio notebooks.

Which solution will meet this requirement?

A. Use Amazon Inspector to monitor SageMaker Studio.

B. Use Amazon Macie to monitor SageMaker Studio.

C. Configure SageMaker to use a VPC with an S3 endpoint.

D. Configure SageMaker to use S3 Glacier Deep Archive.

27. A company is using domain-specific models. The company wants to avoid creating new models from the beginning. The company instead wants to adapt pre-trained models to create models for new, related tasks.

Which ML strategy meets these requirements?

A. Increase the number of epochs.

B. Use transfer learning.

C. Decrease the number of epochs.

D. Use unsupervised learning.

28. A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source.

Which solution meets these requirements?

A. Build a speech recognition system.

B. Create a natural language processing (NLP) named entity recognition system.

C. Develop an anomaly detection system.

D. Create a fraud forecasting system.

29. A company wants to use a large language model (LLM) to develop a conversational agent. The company needs to prevent the LLM from being manipulated with common prompt engineering techniques to perform undesirable actions or expose sensitive information.

Which action will reduce these risks?

30. A company is developing a new model to predict the prices of specific items. The model performed well on the training dataset. When the company deployed the model to production, the model's performance decreased significantly.

What should the company do to mitigate this problem?

31. A company wants to create a chatbot by using a foundation model (FM) on Amazon Bedrock. The FM needs to access encrypted data that is stored in an Amazon S3 bucket. The data is encrypted with Amazon S3 managed keys (SSE-S3).

The FM encounters a failure when attempting to access the S3 bucket data.

Which solution will meet these requirements?

32. A company has a foundation model (FM) that was customized by using Amazon Bedrock to answer customer queries about products. The company wants to validate the model's responses to new types of queries. The company needs to upload a new dataset that Amazon Bedrock can use for validation.

Which AWS service meets these requirements?

33. A company wants to assess the costs that are associated with using a large language model (LLM) to generate inferences. The company wants to use Amazon Bedrock to build generative AI applications.

Which factor will drive the inference costs?

34. An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email message notifications when an ISV's compliance reports become available.

Which AWS service can the company use to meet this requirement?

35. 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?

36. 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?

37. 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?

38. Which functionality does Amazon SageMaker Clarify provide?

39. 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?

40. 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

41. 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

42. 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

43. A 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.

44. An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms.

What should the firm do when developing and deploying the LLM? (Select TWO.)

A. Include fairness metrics for model evaluation.

B. Adjust the temperature parameter of the model.

C. Modify the training data to mitigate bias.

D. Avoid overfitting on the training data.

E. Apply prompt engineering techniques.

45. A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly.

Which evaluation metric should the company use to measure the model's performance?

46. A large retailer receives thousands of customer support inquiries about products every day. The customer support inquiries need to be processed and responded to quickly. The company wants to implement Agents for Amazon Bedrock.

What are the key benefits of using Amazon Bedrock agents that could help this retailer?

47. A company is training a foundation model (FM). The company wants to increase the accuracy of the

model up to a specific acceptance level.

Which solution will meet these requirements?

48. A company has built a chatbot that can respond to natural language questions with images. The company wants to ensure that the chatbot does not return inappropriate or unwanted images.

Which solution will meet these requirements?

49. A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents.

Which solution meets these requirements?

50. A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output.

Which ML algorithm meets these requirements?

51. A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company's security policy states that each team can access data for only the team's own customers.

Which solution will meet these requirements?

52. 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

53. 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?

54. An AI practitioner is building a model to generate images of humans in various professions. The AI practitioner discovered that the input data is biased and that specific attributes affect the image generation and create bias in the model.

Which technique will solve the problem?

55. A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately.

Which Amazon SageMaker inference option will meet these requirements?