1500 Questions | AWS Certified AI Practitioner 2026

Domain 2: Data Science and AI/ML Methodologies (20%): Deep dives into model interpretation, forecasting, NLP, and various classification techniques.

Domain 3: Business Value and Governance (30%): Strategic focus on ROI analysis, project management, and the critical importance of Ethics and Bias in AI.

Domain 4: AI Services and Capabilities (10%): Functional knowledge of AWS-specific tools like Amazon SageMaker, Rekognition, and Textract.

B. Amazon SageMaker Ground Truth

C. Amazon Comprehend Medical

D. AWS Glue

E. Amazon S3

F. Amazon EC2 G4 Instances

Correct Answer: C

Explanation:

A (Incorrect): Rekognition is for image and video analysis, not text-based NLP.

B (Incorrect): Ground Truth is used for labeling raw data, not for the automated extraction of medical entities.

D (Incorrect): Glue is an ETL (Extract, Transform, Load) service, not a pre-trained AI service for medical text.

E (Incorrect): S3 is a storage service and does not have native NLP intelligence.

F (Incorrect): EC2 instances provide the compute power but do not include the pre-built AI models for medical extraction.

Question 2: During the "Business Value and Governance" phase of an AI project, why is it critical to perform a Bias Audit on your training datasets?

B. To ensure the model does not produce discriminatory or unfair outcomes.

C. To make the model run faster on mobile devices.

D. To automatically convert Python code into Java.

E. To bypass the need for data labeling.

F. To decrease the number of features in the dataset.

Correct Answer: B

Explanation:

A (Incorrect): Auditing for bias is a quality and ethics step, not a strategy to increase costs.

C (Incorrect): Bias auditing relates to fairness and accuracy, not the hardware performance or latency of the model.

D (Incorrect): Bias audits have nothing to do with programming language translation.

E (Incorrect): Auditing actually often requires more careful labeling, not less.

F (Incorrect): Reducing features is "Dimensionality Reduction," which is a different technical process.

Question 3: Which machine learning methodology is most appropriate for predicting future stock prices based on five years of historical price data?

B. Object Detection

C. Time-Series Forecasting

D. Sentiment Analysis

E. Generative Adversarial Networks (GANs)

F. Unsupervised Clustering

Correct Answer: C

Explanation:

A & B (Incorrect): These are computer vision tasks used for visual data, not numerical price data.

D (Incorrect): Sentiment analysis gauges emotion in text; while it can influence stocks, it isn't the method for predicting the prices themselves.

E (Incorrect): GANs are used to generate new data (like images), not typically for standard financial forecasting.

F (Incorrect): Clustering finds hidden patterns in data but doesn't predict specific future numerical values.

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