Free Oracle Cloud Infrastructure 2025 AI Foundations Associate Practice Test

A retail company wants to implement a solution that can automatically categorize customer support tickets based on their content. Which type of AI task would best address this requirement?

An organization is evaluating different AI approaches. They need a system that can learn from historical data with labeled examples showing correct outcomes. Which machine learning approach should they use?

A data scientist notices that their model performs exceptionally well on training data but poorly on new, unseen data. What problem is the model experiencing?

Which OCI AI Service would be most appropriate for extracting text from scanned invoices and receipts to automate data entry processes?

What is the primary characteristic that distinguishes Generative AI from other types of AI?

A healthcare provider wants to analyze patient feedback from multiple sources including emails, chat logs, and survey responses to understand sentiment trends. Which OCI AI Service should they implement?

In the context of machine learning model development, what is the primary purpose of using a validation dataset that is separate from both training and test datasets?

A company needs to detect anomalies in their manufacturing sensor data to predict equipment failures. The data shows normal operation patterns with occasional irregular readings. Which OCI AI Service is best suited for this use case?

When implementing a Large Language Model (LLM) for a customer service chatbot, what technique allows you to provide specific context or instructions to guide the model's responses without retraining it?

A data scientist is evaluating a binary classification model and notices it has 95% accuracy, but the dataset has 95% of one class and 5% of the other. What is the most appropriate metric to better evaluate this model's performance?

An e-commerce company wants to implement a solution that can automatically generate product descriptions from product images and attributes. Which combination of OCI AI Services would be most effective?

What is the primary advantage of using transfer learning in machine learning projects?

In the context of AI ethics and responsible AI, what does the principle of 'explainability' refer to?

A company is implementing an OCI Speech service to transcribe customer service calls. They need to improve accuracy for industry-specific terminology. What feature should they utilize?

When working with Large Language Models, what phenomenon occurs when the model generates plausible-sounding but factually incorrect information?

An organization is designing an AI solution that needs to process customer data. Which of the following is NOT a key consideration for responsible AI implementation?

A financial services company wants to use OCI AI services to analyze loan applications. They need to extract key entities like names, dates, monetary amounts, and addresses from application documents, and also determine the sentiment of applicant statements. What is the most efficient approach?

A data science team is experiencing model performance degradation in production despite excellent validation results during development. Upon investigation, they discover that the distribution of incoming production data has shifted significantly from the training data distribution. What is this phenomenon called, and what is the best approach to address it?

An organization wants to implement a Generative AI solution but is concerned about potential misuse and harmful outputs. They need to implement safeguards. Which combination of techniques would be most effective?

A machine learning team needs to optimize a model's hyperparameters but has limited computational resources. They have dozens of potential hyperparameter combinations to test. Which approach would be most efficient while still finding good hyperparameter values?