Free Microsoft AI-900 Exam Dumps Questions & Answers

Which term is used to describe uploading your own data to customize an Azure OpenAI model?

• A.fine -tuning
• B.prompt engineering
• C.completion
• D.grounding

You plan to use Azure Cognitive Services to develop a voice controlled personal assistant app.
Match the Azure Cognitive Services to the appropriate tasks.
To answer, drag the appropriate service from the column on the left to its description on the right Each service may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:

According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn Cognitive Services documentation, developing a voice-controlled personal assistant app involves integrating multiple Azure AI services that specialize in different aspects of language and speech processing. The three services in focus-Azure AI Speech, Azure AI Language Service, and Azure AI Translator Text-perform unique but complementary roles in conversational AI systems.
* Convert a user's speech to text # Azure AI SpeechThe Azure AI Speech service provides speech-to-text (STT) capabilities. It enables applications to recognize spoken language and convert it into written text in real time. This is often the first step in voice-enabled applications, transforming audio input into a machine-readable format that can be analyzed further.
* Identify a user's intent # Azure AI Language serviceOnce speech has been transcribed, the Azure AI Language service (which includes capabilities like Conversational Language Understanding and Text Analytics) interprets the meaning of the text. It detects the user's intent (what the user wants to accomplish) and extracts entities (key data points) from the input. This service helps the assistant understand commands like "Book a flight" or "Set a reminder."
* Provide a spoken response to the user # Azure AI SpeechAfter determining an appropriate response, the system uses the text-to-speech (TTS) feature of Azure AI Speech to convert the assistant's text-based reply back into natural-sounding spoken language, allowing the user to hear the response.
Together, these services form the backbone of a conversational AI system: Speech-to-Text # Language Understanding # Text-to-Speech, aligning precisely with the AI-900 curriculum's explanation of how Azure Cognitive Services enable intelligent voice-based interactions.

Select the answer that correctly completes the sentence.

Correct Answer:

Explanation:

According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore fundamental principles of machine learning," regression is a supervised machine learning technique used to predict continuous numeric values based on input data.
In this scenario, the goal is to predict how many hours of overtime a delivery person will work depending on the number of orders received. The output - the number of overtime hours - is a continuous variable (for example, 1.5 hours, 3.2 hours, etc.), not a category. This makes it a regression problem, where the model learns patterns from historical data and uses those patterns to estimate a continuous numeric outcome.
Why Regression Applies Here:
Regression models work by finding the mathematical relationship between input features (independent variables) and output values (dependent variables). In this case:
* Input (feature): Number of orders received
* Output (label): Predicted overtime hours
Azure Machine Learning supports several regression algorithms, including Linear Regression, Decision Tree Regression, and Neural Network Regression, all of which can handle scenarios where a numeric prediction is required.
Why Not the Other Options:
* Classification: Used for predicting discrete categories or labels (e.g., "on-time" vs. "late"). It does not output continuous numbers.
* Clustering: An unsupervised learning technique used to group data points with similar characteristics, not to make numeric predictions.
Thus, when the output variable is a numeric prediction (such as hours, prices, quantities, or time), the correct machine learning task is Regression.

You ate building a Conversational Language Understanding model for an e-commerce business.
You need to ensure that the model detects when utterances are outside the intended scope of the model.
What should you do?

• A.Create a prebuilt task entity.
• B.Create a new model.
• C.Export the model.
• D.Add utterances to the None intent.

To complete the sentence, select the appropriate option in the answer area.

Correct Answer:

Explanation:

According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Identify features of regression machine learning", regression is a type of supervised machine learning used when the target variable (the value you want to predict) is a continuous numeric value.
In this scenario, the task is to predict how many hours of overtime a delivery person will work based on the number of orders received. Both the input (number of orders) and the output (hours of overtime) are numeric variables. Since the goal is to estimate a quantitative value rather than categorize or group data, this is a classic example of a regression problem.
Regression models analyze the relationship between variables to make numerical predictions. For example, the model might learn that each additional 20 orders increases overtime by about two hours. Common algorithms used for regression include linear regression, decision tree regression, and boosted regression models. These models produce outputs such as "expected overtime = 5.6 hours," which are continuous numeric results.
To contrast with the other options:
* Classification is used for predicting categories or labels, such as "overtime required" vs. "no overtime," or "high-risk" vs. "low-risk." It deals with discrete outputs rather than continuous numbers.
* Clustering is an unsupervised learning approach used to group similar data points based on shared characteristics, such as grouping delivery staff by performance patterns or customer types.
As emphasized in Microsoft's Responsible AI and Machine Learning Fundamentals learning paths, regression models are ideal for numeric forecasting problems such as predicting sales, revenue, demand, or working hours.
Therefore, the correct answer is: Regression.
Reference:Microsoft Learn - Identify the types of machine learning models: Regression, Classification, and Clustering (AI-900 Learning Path)