IBM A1000-076 - Assessment: Foundations of AI Practice Exam: Test Your Knowledge 2025

What is the primary difference between Artificial Intelligence (AI) and Machine Learning (ML)?

A retail company wants to automatically categorize customer support emails into predefined categories such as 'Shipping Issues,' 'Product Defects,' and 'Billing Questions.' What type of machine learning problem is this?

Which IBM Watson service would be most appropriate for extracting insights from unstructured text data, such as sentiment, emotion, and entities?

What is a key ethical concern when deploying AI systems in hiring and recruitment processes?

In the context of neural networks, what is the purpose of an activation function?

A data scientist notices that their machine learning model performs exceptionally well on training data (98% accuracy) but poorly on test data (65% accuracy). What problem is the model experiencing?

What is the primary purpose of the 'confidence score' returned by many IBM Watson AI services?

A healthcare provider wants to implement an AI system for diagnostic assistance. Which principle should be prioritized to ensure responsible AI deployment?

In the context of AI, what does the term 'ground truth' refer to?

A company is building a Watson Assistant chatbot for customer service. What is the purpose of 'intents' in Watson Assistant?

What is the primary difference between supervised and unsupervised learning?

A financial services company wants to detect fraudulent transactions in real-time. The fraud patterns are constantly evolving, and labeled examples of fraud are rare. What approach would be most appropriate?

When implementing IBM Watson services in a production environment, what is the recommended approach for handling API credentials and authentication?

What is the purpose of a validation dataset in machine learning model development?

A manufacturing company wants to implement predictive maintenance using AI. Which type of data would be LEAST useful for this application?

In deep learning, what is the vanishing gradient problem and in which type of architecture does it commonly occur?

A global company is deploying a Watson Natural Language Understanding solution to analyze customer feedback in multiple languages. What consideration is most important for ensuring fair and accurate results across different languages?

What is the primary purpose of feature engineering in machine learning?

A company is developing an AI system that will make loan approval decisions. To ensure responsible AI implementation, what practice should be implemented?

In a Watson Assistant dialog flow, what is the purpose of 'slots' functionality?