AI-900 Practice Test 10 — 10 Questions

Question 1

What is AutoML in Azure Machine Learning and what does it automate?

Accepted Answer

Automatically selecting algorithms, engineering features, and tuning hyperparameters to find the best model. AutoML in Azure Machine Learning automates the iterative process of algorithm selection, feature engineering, and hyperparameter tuning to identify the best-performing model for a given dataset. It systematically evaluates multiple machine learning pipelines and returns the model with the highest metric score, reducing manual trial-and-error. This helps data scientists and non-experts build high-quality models efficiently.

Answer

Automatically deploying models to production without human review

Answer

Automatically collecting and labeling training data from the internet

Answer

Automatically writing Python code for custom ML algorithms

Question 2

What is the 'mean absolute error' (MAE) metric used to evaluate in machine learning?

Accepted Answer

The average absolute difference between regression model predictions and actual values. Mean Absolute Error (MAE) is a regression metric that calculates the average of the absolute differences between predicted and actual values. It measures how close predictions are to the true outcomes, with lower values indicating better model accuracy. In Azure Machine Learning, MAE is commonly used to evaluate regression models like linear regression or decision forests.

Answer

The average confidence percentage of classification predictions

Answer

The proportion of model predictions that deviate from expected values by more than a threshold

Answer

How much the model's predictions differ from random chance

Question 3

A meeting transcription service needs to convert multilingual audio recordings into accurate text in real time. Which Azure OpenAI Service model is specifically designed for this task?

Accepted Answer

Whisper. Whisper is the Azure OpenAI Service model specifically designed for speech-to-text transcription, including multilingual audio recordings, and it supports real-time conversion. Unlike GPT-4, which is a large language model for text generation, Whisper is optimized for audio processing tasks such as transcription and translation. This makes it the correct choice for converting multilingual audio into accurate text in real time.

Answer

GPT-4

Answer

DALL-E 2

Answer

Codex

Question 4

What is 'Azure AI Foundry's model hub' and what models are available there?

Accepted Answer

A curated collection of leading AI models from OpenAI, Microsoft (Phi), Meta, Mistral, and others. Azure AI Foundry's model hub is a curated collection of leading AI models from providers like OpenAI, Microsoft (Phi), Meta, Mistral, and others. It enables developers to discover, compare, and deploy pre-built models for generative AI workloads without needing to train models from scratch. This aligns with the exam's focus on leveraging existing AI services in Azure.

Answer

A marketplace where organisations can sell their custom-trained AI models to other Azure customers

Answer

A version control system for AI models similar to Git for code

Answer

A centralised repository of Microsoft's internal research models not available to customers

Question 5

A medical research organization uses an AI system to analyze patient health records to identify patterns in disease progression. They publish a research paper that includes tables of aggregated statistics derived from the data. Later, a researcher discovers that by combining multiple statistics, it is possible to identify individual patients. Which Microsoft responsible AI principle has been most directly compromised?

Accepted Answer

Privacy and security. The scenario describes a re-identification attack, where aggregated statistics (tables) can be combined to infer individual patient identities. This directly violates the privacy and security principle, which requires that AI systems protect personal data and prevent unauthorized identification. Microsoft's responsible AI principle of privacy and security emphasizes safeguarding data through techniques like differential privacy, which was not applied here.

Answer

Fairness

Answer

Transparency

Answer

Accountability

Question 6

What does the Azure AI Translator's language detection feature do when no source language is specified?

Accepted Answer

It automatically detects the source language and includes it in the translation response. When no source language is specified in Azure AI Translator, the language detection feature automatically identifies the language of the input text and includes the detected language code in the translation response. This is a core capability of the service, enabling seamless translation without requiring the user to pre-identify the source language.

Answer

It refuses to translate and returns an error

Answer

It defaults to English as the assumed source language

Answer

It translates the text into every supported language

Question 7

Which of the following scenarios is an example of a recommendation system AI workload?

Accepted Answer

A music streaming service suggesting new songs based on listening history. A recommendation system AI workload analyzes user behavior (e.g., listening history) to predict and suggest new items (songs) that the user is likely to enjoy. This is a classic example of a collaborative filtering or content-based filtering model, which is a core AI workload under the 'Predictive' or 'Personalization' category.

Answer

A spelling checker that identifies misspelled words in a document

Answer

A database storing customer purchase history

Answer

A barcode scanner at a checkout counter

Question 8

What is a common use case for AI-powered virtual assistants or chatbots in enterprise settings?

Accepted Answer

Automating first-line support by answering common questions 24/7. AI-powered virtual assistants and chatbots are commonly deployed in enterprise settings to handle first-line support inquiries, such as FAQs, password resets, or order status checks, operating 24/7 without human intervention. This reduces the workload on human agents by automating routine, high-volume interactions, allowing them to focus on complex issues. The technology relies on natural language processing (NLP) and intent recognition to understand user queries and provide predefined or dynamically generated responses.

Answer

Replacing all human customer service employees permanently

Answer

Making autonomous business decisions without human oversight

Answer

Monitoring employee productivity in real time

Question 9

A marketing team wants to generate unique product images by providing detailed textual descriptions. Which Azure OpenAI model should they use?

Accepted Answer

DALL-E. DALL-E is the correct Azure OpenAI model because it is specifically designed to generate images from textual descriptions. It uses a diffusion-based architecture to create high-quality, unique images based on detailed prompts, making it ideal for the marketing team's requirement.

Answer

GPT-4

Answer

Codex

Answer

Whisper

Question 10

What is 'healthcare NLP' in Azure AI Language and what medical entities can it extract?

Accepted Answer

Extracting diagnoses, medications, symptoms, procedures, and lab results from clinical text. Healthcare NLP in Azure AI Language is a specialized feature designed to extract structured medical information from unstructured clinical text, such as physician notes or discharge summaries. It uses pre-trained models to identify entities like diagnoses, medications, symptoms, procedures, and lab results, enabling downstream analytics and decision support. Option B correctly describes this capability.

Answer

Translating medical terminology between different languages for international patients

Answer

Generating medical reports from structured patient data in an EHR system

Answer

Diagnosing patient conditions from their described symptoms using AI