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Free AWS Certified AI Practitioner Exam Practice Questions

Question # 61

A company is deploying an AI-powered loan approval system. The company must comply with data governance regulations for AI.

Which solution will meet these requirements?

Options:

A.  

Modify AI outputs based on user preferences without audit trails.

B.  

Implement data lifecycle management to track and manage AI training data.

C.  

Prioritize AI inference-time optimization over data residency requirements.

D.  

Use only synthetic data for model training to avoid compliance risks.

Discussion 0
Question # 62

A customer service team is developing an application to analyze customer feedback and automatically classify the feedback into different categories. The categories include product quality, customer service, and delivery experience.

Which AI concept does this scenario present?

Options:

A.  

Computer vision

B.  

Natural language processing (NLP)

C.  

Recommendation systems

D.  

Fraud detection

Discussion 0
Question # 63

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?

Options:

A.  

Create an Amazon Bedrock custom service role for each team that has access to only the team ' s customer data.

B.  

Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each Amazon Bedrock request.

C.  

Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.

D.  

Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each team that have access to only each team ' s customer folders.

Discussion 0
Question # 64

A company uses foundation models (FMs) to automate daily tasks. An AI practitioner is creating system instructions that include context relevant to the tasks. The AI practitioner wants to save and reuse the instructions in daily interactions with FMs in Amazon Bedrock.

Which Amazon Bedrock solution will meet these requirements?

Options:

A.  

Knowledge Bases

B.  

Guardrails

C.  

Playgrounds

D.  

Prompt management

Discussion 0
Question # 65

A manufacturing company has an application that ingests consumer complaints from publicly available sources. The application uses complex hard-coded logic to process the complaints. The company wants to scale this logic across markets and product lines.

Which advantage do generative AI models offer for this scenario?

Options:

A.  

Predictability of outputs

B.  

Adaptability

C.  

Less sensitivity to changes in inputs

D.  

Explainability

Discussion 0
Question # 66

A company is building an AI application to automate business processes. The company uses a foundation model (FM) to support the application.

The company needs to select datasets to assess the quality of the AI model ' s behavior.

Which type of datasets will meet these requirements?

Options:

A.  

Curated datasets that have had all outliers and correlations removed

B.  

Synthetic datasets that have been generated by the newest FM

C.  

Diverse datasets that cover various use cases and usage scenarios

D.  

Randomized datasets that have arbitrary features and skewed distributions

Discussion 0
Question # 67

Which component of Amazon Bedrock Studio can help secure the content that AI systems generate?

Options:

A.  

Access controls

B.  

Function calling

C.  

Guardrails

D.  

Knowledge bases

Discussion 0
Question # 68

A company has developed a neural network model to replace an existing decision tree model. The neural network model has a higher prediction accuracy compared to the decision tree model. However, the neural network model’s decision process is not as explainable as the decision tree model’s decision process.

Which tradeoff is the company making by adopting the neural network model?

Options:

A.  

Higher compliance for lower interpretability

B.  

Higher performance for lower portability

C.  

Higher performance for lower interpretability

D.  

Higher portability for lower interpretability

Discussion 0
Question # 69

A software company wants to use a large language model (LLM) for workflow automation. The application will transform user messages into JSON files. The company will use the JSON files as inputs for data pipelines.

The company has a labeled dataset that contains user messages and output JSON files.

Which solution will train the LLM for workflow automation?

Options:

A.  

Unsupervised learning

B.  

Continued pre-training

C.  

Fine-tuning

D.  

Reinforcement learning from human feedback (RLHF)

Discussion 0
Question # 70

A company is using Amazon Bedrock to answer questions. The Amazon Bedrock foundation model (FM) uses the company ' s internal documentation to respond to the questions. The documentation is updated frequently. The company needs a solution that avoids recurring costs for model training while keeping responses current.

Which solution will meet these requirements?

Options:

A.  

Use Amazon Bedrock Knowledge Bases with Retrieval Augmented Generation (RAG) when responding to questions.

B.  

Use Amazon Bedrock model customization to fine-tune the FM after each documentation update.

C.  

Use prompt engineering with static examples embedded in the prompt that reference the initial documentation.

D.  

Cache the previous responses and reuse the responses for similar questions without checking for documentation updates.

Discussion 0

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