Microsoft Azure AI Fundamentals Practice Exam: Test Your Knowledge 2025

A healthcare organization is developing an AI system to assist doctors in diagnosing diseases from medical images. Which principle of Responsible AI should be the PRIMARY focus to ensure the system provides clear reasoning for its diagnostic suggestions?

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

A retail company wants to automatically analyze customer feedback images posted on social media to identify their products and detect brand logos. Which Azure Cognitive Service should they use?

A company is building a chatbot that needs to understand user intent from text messages and extract key information like dates, locations, and product names. Which Azure service provides this capability?

Which Azure service enables you to create applications that can generate human-like text, code, and images based on natural language prompts?

A financial services company must ensure their AI system treats all demographic groups fairly when evaluating loan applications. They notice the model performs differently across various age groups. What should they do to address this issue?

You are training a machine learning model and notice that it performs exceptionally well on training data (98% accuracy) but poorly on test data (65% accuracy). What problem is the model experiencing?

A manufacturing company wants to identify defective products on an assembly line by analyzing images in real-time. They have very few examples of defective products. Which Azure service feature would be MOST appropriate for this scenario?

You need to implement a solution that can analyze customer service call recordings to determine customer sentiment, identify topics discussed, and extract key phrases. Which combination of Azure Cognitive Services features would be MOST appropriate?

A company wants to use a generative AI model to create product descriptions but is concerned about the model generating inappropriate or inaccurate content. What technique should they implement to help ensure responsible outputs?

Which AI workload is characterized by the system learning from interactions with an environment to maximize a reward signal, without being explicitly told which actions to take?

You are using Azure Machine Learning to train a regression model to predict house prices. Which metric would be MOST appropriate to evaluate your model's performance?

A security company needs to analyze surveillance video footage to detect when people enter restricted areas and identify if they are wearing required safety equipment. Which Azure service would provide the MOST comprehensive solution?

A global e-commerce platform needs to provide customer support in multiple languages. They want to automatically detect the language of incoming customer messages, translate them to English for their support team, and translate responses back to the customer's language. Which Azure service combination would be MOST efficient?

When using Azure OpenAI Service for generating content, what is the purpose of 'temperature' as a parameter in the model configuration?

A company is implementing an AI system for automated resume screening. Which Responsible AI principle should they prioritize to ensure the system doesn't discriminate against candidates based on protected characteristics?

In Azure Machine Learning, you need to split your dataset to properly evaluate model performance. You have 10,000 labeled examples. What is the recommended approach for dividing this data?

A museum wants to create an application that allows visually impaired visitors to understand artwork through audio descriptions. The app should analyze paintings and generate descriptive text about what's shown. Which Azure services would work together to accomplish this?

You are building a virtual assistant that needs to understand complex multi-turn conversations, remember context from earlier in the dialogue, and extract entities mentioned throughout the conversation. Which Azure service feature is specifically designed for this conversational scenario?

When implementing retrieval augmented generation (RAG) with Azure OpenAI Service, what is the PRIMARY benefit of this approach compared to using the language model alone?