Download Latest AI-901 Questions

A multimodal model can receive a single user prompt that includes the image plus instructions. The prompt can ask for both outputs in one request, for example: “Analyze this image and provide a written summary and an audio summary.” Therefore, the minimum number of user prompts is 1 .

The REST API request contains an image-generation style payload:

{

" prompt " : " A polar bear on the beach holding an icecream " ,

" size " : " 1024x1024 " ,

" n " : 1,

" style " : " vivid "

}

This request asks the model to generate an image from a text prompt. In Azure OpenAI, DALL-E models are used for image generation from natural language prompts.

Why the other options are incorrect:

B. Codex is associated with code generation tasks.

C. GPT-4.1 is primarily used for text/chat and multimodal reasoning, not this classic image-generation API payload.

D. Whisper is used for speech-to-text transcription.

The correct answer is classify email messages as work-related or personal . Natural language processing (NLP) is concerned with analyzing, interpreting, and processing human language, including unstructured text contained in documents, messages, reviews, and emails. Text classification is therefore a direct NLP workload: an AI model analyzes the linguistic content of an email and assigns it to a predefined category such as work-related or personal .

Microsoft ' s current AI-901 study guide explicitly requires candidates to identify scenarios for common AI workloads, including text analysis , and to understand common text-analysis techniques. Microsoft Azure Language in Foundry Tools similarly supports capabilities for extracting information from text and classifying text , demonstrating that categorization based on textual content is an NLP function.

Predicting future car rentals is primarily a regression/forecasting problem because the output is a numerical quantity. Predicting whether a website visitor will transact is typically a binary classification machine-learning problem based on behavioral or transactional features, not necessarily language. Stopping industrial machinery when a temperature threshold is exceeded is a rule-based monitoring/control scenario.