Free IBM A1000-047 - Assessment: Foundations of AI Practice Test
A1000-047
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What is the primary difference between Artificial Intelligence (AI) and Machine Learning (ML)?
A healthcare organization wants to use IBM Watson to analyze patient medical records and assist doctors in diagnosing diseases. Which IBM Watson service would be most appropriate for this use case?
In supervised learning, what is the role of labeled training data?
Which ethical principle emphasizes that AI systems should be designed to be understandable and their decisions explainable to users and stakeholders?
What type of machine learning is used when an AI agent learns to play a game by receiving rewards for good moves and penalties for bad moves?
A retail company wants to implement a chatbot that can handle customer inquiries about product availability, order status, and return policies. Which IBM Watson service should they primarily use?
What is the primary purpose of a neural network's activation function?
Which of the following best describes 'Natural Language Processing' (NLP)?
A financial institution is developing an AI system for loan approval. They discover that the model consistently denies loans to applicants from certain demographic groups. What AI ethics principle is being violated?
What is the difference between narrow AI (weak AI) and general AI (strong AI)?
A data scientist is building a classification model and notices that the model performs exceptionally well on training data (99% accuracy) but poorly on test data (65% accuracy). What problem is the model experiencing?
Which IBM Watson service would be most appropriate for extracting entities, keywords, sentiment, and categories from unstructured text data?
In the context of AI governance, what is the purpose of a 'model card' or 'AI factsheet'?
What is the primary purpose of feature engineering in machine learning?
A company wants to use IBM Watson Studio to collaborate on data science projects. What is a primary benefit of using Watson Studio for their team?
What is 'computer vision' in the context of artificial intelligence?
An organization is implementing AI systems and wants to ensure they can track and audit all AI-related decisions for compliance purposes. Which AI governance practice would best support this requirement?
In a deep learning neural network, what happens during the backpropagation process?
A company is developing an AI-powered recommendation system that will process personal user data. To comply with privacy regulations and ethical AI principles, which approach should they prioritize?
A data science team is working on a multi-class classification problem with imbalanced classes (Class A: 90% of data, Class B: 8%, Class C: 2%). Which evaluation metric would be most appropriate for assessing model performance?
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