IBM A1000-074: Assessment: Foundations of Watson AI v2 Practice Exam: Test Your Knowledge 2025

A retail company wants to build a chatbot that can understand customer inquiries in natural language and provide relevant responses. Which IBM Watson service is most appropriate for this use case?

What is the primary difference between supervised and unsupervised machine learning?

A developer is integrating Watson Assistant into a mobile application. What is the recommended authentication method for securing API calls to Watson services?

Which Watson service would be most appropriate for analyzing customer feedback from surveys to identify overall sentiment and emotional tone?

In the context of AI ethics, what is meant by 'bias' in machine learning models?

A healthcare organization needs to extract and analyze information from thousands of medical research papers. Which Watson service combination would be most effective?

When developing a Watson Assistant chatbot, what is the purpose of 'intents'?

What is 'overfitting' in machine learning, and why is it a concern?

A developer is building an application that needs to convert customer service phone calls into text for analysis. After transcription, the application should identify key topics and sentiment. What is the correct sequence of Watson services to use?

In Watson Natural Language Understanding, what are 'entities'?

A financial services company wants to ensure their AI model decisions are explainable and transparent to regulators. Which IBM capability addresses this requirement?

What is the primary purpose of 'dialog' in Watson Assistant?

Which type of machine learning algorithm would be most appropriate for grouping customers into segments based on purchasing behavior without predefined categories?

A Watson Assistant is returning incorrect responses for user queries. During troubleshooting, a developer notices that multiple intents have very similar training examples. What is the most likely issue and recommended solution?

What is 'transfer learning' in the context of deep learning and Watson services?

An e-commerce company wants to implement an AI solution that automatically tags product images with relevant categories and attributes. Which Watson service should they use?

In a Watson Assistant implementation, a company needs to handle sensitive customer information like account numbers. What is the best practice for managing this data?

What is the primary advantage of using Watson Knowledge Studio in conjunction with Watson Natural Language Understanding?

A company is evaluating whether to build a custom AI model or use a pre-trained Watson service. Which factor would most strongly suggest using a pre-trained Watson service?

In a production Watson Assistant deployment, the bot's response times have become unacceptably slow during peak hours. What architectural approach would best address this performance issue?