AI-900 Describe features of generative AI workloads on Azure — All Questions With Answers

Question 1easymultiple choice

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A marketing team wants to use Azure AI to automatically generate unique product descriptions for thousands of items in an e-commerce catalog based on a few keywords provided by the inventory team. Which Azure service should they use?

Question 2mediummultiple choice

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A company is developing a chatbot that can both answer customer questions in natural language and create images on demand (e.g., 'Generate a picture of a product prototype'). Which combination of Azure generative AI models should they integrate?

Question 3mediummultiple choice

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A game development company uses Azure OpenAI Service to automatically generate in-game dialog for non-player characters (NPCs) based on character profiles. They need to ensure the generated text does not contain offensive language or harmful suggestions. Which Azure OpenAI Service feature should they configure to prevent this?

Question 4hardmultiple choice

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A company uses Azure OpenAI Service to generate marketing copy for social media posts. They want to prevent the model from producing content that contains offensive language, harmful stereotypes, or violent themes that go against their brand guidelines. Which feature should the company configure within Azure OpenAI Service?

Question 5mediummultiple choice

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A company uses Azure OpenAI Service to power a chat-based support assistant. They have extensive knowledge base documents that contain the correct information. The company wants the assistant to answer questions solely based on the provided documents and avoid generating plausible-sounding but incorrect information. Which approach should they implement to minimize the risk of such fabrications?

Question 6easymultiple choice

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A marketing team uses Azure OpenAI Service to generate multiple variations of a product description from a single prompt. They want the generated descriptions to be more creative and diverse, rather than repetitive. Which parameter should they increase to achieve this?

Question 7mediummultiple choice

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A company uses Azure OpenAI Service to power an AI assistant that helps customers with product troubleshooting. The assistant must maintain the conversation history to provide contextually relevant answers across multiple turns. Which API endpoint should be used for this purpose?

Question 8hardmultiple choice

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A marketing agency wants to use Azure OpenAI Service to generate product descriptions that consistently match a client's distinctive brand voice. They have a collection of 50 sample descriptions written in the desired tone and style. Which Azure OpenAI Service capability should they use to specialize the model to produce text that closely matches this style?

Question 9mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate headline ideas for a campaign. They find the generated headlines are often too similar and lack creativity. Which parameter should they increase to introduce more randomness in the generated text?

Question 10mediummultiple choice

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A game development studio uses Azure OpenAI Service to generate unique backstories for non-player characters (NPCs). They want the generated stories to be coherent and relevant to a given character class (e.g., warrior, mage) but also creative and varied. Which parameter should the studio adjust primarily to increase the creativity and variety of the generated text?

Question 11mediummultiple choice

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A marketing team wants to use Azure OpenAI Service to generate product descriptions that consistently match a specific brand voice. They have a small set of example descriptions that demonstrate the desired tone. They want to adapt the model without retraining it from scratch. Which approach should they take?

Question 12mediummultiple choice

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A company uses Azure OpenAI Service to generate long technical reports. To manage costs, the development team needs to accurately estimate the number of tokens that a given prompt will consume before making any API call. Which Azure OpenAI Service feature should they use to obtain this estimate?

Question 13easymultiple choice

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A developer is using Azure OpenAI Service to generate product descriptions. They want the output to be highly focused and deterministic, with less randomness. Which parameter should they decrease?

Question 14easymultiple choice

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A developer is using Azure OpenAI Service to generate Python code snippets. They notice that the generated code often contains repetitive function definitions and loops. Which parameter should be increased to reduce this repetition?

Question 15mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate marketing copy. They notice the generated text is often repetitive, using the same phrases and words multiple times. Which parameter should they increase to directly reduce this repetition?

Question 16hardmultiple choice

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A quality assurance team at a software company uses Azure OpenAI Service to generate compliance reports. They need the model to produce the exact same output for a given prompt every time the API is called, to ensure reproducibility during testing. Which parameter should they set to achieve this deterministic behavior?

Question 17easymultiple choice

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A developer uses Azure OpenAI Service to generate creative marketing copy. The API costs are based on the total number of tokens processed (input + output). To minimize costs, the developer wants to ensure that the generated text is as brief as possible while still being effective. Which parameter should the developer adjust in the API request?

Question 18easymultiple choice

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A developer uses Azure OpenAI Service to generate product descriptions. Each description must be concise and not exceed 50 words. Which parameter should the developer set in the API request to control the output length?

Question 19mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate social media posts. They want the generated text to be more creative and diverse, with unexpected word choices. Which parameter should they increase?

Question 20mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate tagline options for a new product. They notice that the model often generates very similar taglines for the same prompt, lacking creativity. To increase the diversity and variety of the output, which parameter should they increase?

Question 21mediummultiple choice

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A financial analyst uses Azure OpenAI Service to generate summaries of quarterly earnings reports. The analyst provides the raw text of the report in the prompt and wants the summary to stick strictly to the facts presented in that text, without adding any external information or speculation. Which technique should the analyst employ to minimize the risk of the model inventing information?

Question 22mediummultiple choice

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A writer uses Azure OpenAI Service to generate story ideas. The current configuration uses a temperature setting of 0, causing the model to produce identical outputs for the same prompt. The writer wants more creative and diverse outputs. Which parameter should be increased?

Question 23mediummultiple choice

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A developer uses Azure OpenAI Service to generate code snippets. They need the model to produce the most likely completion each time, with no randomness or creativity. Which parameter should they set?

Question 24easymultiple choice

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A developer uses Azure OpenAI Service to generate product reviews for an e-commerce site. The developer notices that the model often repeats the same phrases within the same review, making the output sound unnatural. Which parameter should the developer adjust to reduce this repetition?

Question 25mediummultiple choice

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A developer uses Azure OpenAI Service to generate multiple alternative product slogans. The developer wants to get exactly 5 different slogan options in a single API call, each being a separate piece of text. Which parameter should the developer set to control the number of completions returned?

Question 26mediummultiple choice

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A developer uses the Azure OpenAI Service to generate product descriptions for an e-commerce catalog. The developer notices that the generated text is often too long, exceeding the desired word count. Which parameter should the developer set in the API request to strictly limit the length of the generated output?

Question 27mediummultiple choice

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A social media company uses Azure OpenAI Service to automatically generate captions for user-uploaded images. The company has a strict content policy that prohibits any generated captions containing profanity, hate speech, or self-harm references. Which feature of the Azure OpenAI Service should the company configure to automatically block such harmful content?

Question 28easymultiple choice

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A developer uses Azure OpenAI Service to generate marketing copy. They want the model to produce more focused and deterministic responses, reducing the variety of outputs for the same prompt. Which parameter should the developer decrease?

Question 29hardmultiple choice

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A legal research firm uses Azure OpenAI Service to answer questions about specific case law documents. They want the model to base its answers exclusively on the content of the provided documents, without using any external knowledge from its training. Which approach should they use?

Question 30mediummultiple choice

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A developer uses Azure OpenAI Service to generate short product descriptions. The developer notices that the model sometimes produces nonsensical or very low-probability words that make the output less coherent. The developer wants to reduce the chance of such outputs while still allowing some creative variability. Which parameter should the developer adjust in the API request?

Question 31easymultiple choice

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A social media platform uses Azure OpenAI Service to generate summaries of user comments. The development team discovers that sometimes the generated summaries include offensive or harmful language that was present in the original comments. The team wants to ensure that the generated output is always free of hate speech, profanity, and self-harm references. What should the team configure in the Azure OpenAI Service?

Question 32easymultiple choice

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A marketing team wants to create original images for advertisements based on text descriptions. Which Azure OpenAI Service model capability should they use?

Question 33mediummultiple choice

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A developer uses Azure OpenAI Service to generate long-form articles. The developer notices that the model tends to repeat the same sentence structures and vocabulary, making the output monotonous. Which parameter should the developer increase to reduce this repetition?

Question 34mediummultiple choice

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A developer is using Azure OpenAI Service to classify customer support tickets into categories such as 'Billing', 'Technical Issue', and 'Account Management'. The developer provides three labeled examples for each category in the prompt to improve the model's accuracy. What technique is the developer applying?

Question 35easymultiple choice

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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?

Question 36mediummultiple choice

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A company uses Azure OpenAI Service to generate product descriptions for an e-commerce site. They want to ensure that the generated descriptions never contain offensive, violent, or hateful content. Which built-in feature should the developer enable in the Azure OpenAI Service?

Question 37hardmultiple choice

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A company uses Azure OpenAI Service to generate creative product descriptions. They want to increase the randomness and variety of the generated outputs to produce more diverse suggestions. Which parameter should they increase?

Question 38easymultiple choice

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A company uses Azure OpenAI Service to generate executive summaries of lengthy reports. The generated summaries sometimes include information that was not present in the original report, making them unreliable. Which Azure OpenAI Service feature should the company use to anchor the model to the provided report content?

Question 39hardmultiple choice

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A developer uses Azure OpenAI Service to generate product descriptions. They want to ensure that the model only considers the most likely tokens that together have a cumulative probability of 0.95, ignoring very low-probability tokens that could lead to nonsensical outputs. Which parameter should they configure?

Question 40hardmultiple choice

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A developer uses Azure OpenAI Service to generate product name suggestions. They want to ensure the model never outputs a specific word, such as 'Corporation', because it is too formal for their brand. Which parameter should the developer configure to reduce the probability of that token being generated?

Question 41mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate taglines for a new advertising campaign. They want the output to be more predictable and less surprising, sticking to the most common phrases and avoiding unusual combinations. Which parameter should they decrease?

Question 42hardmultiple choice

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A developer is using Azure OpenAI Service to generate product descriptions from technical specifications. The generated descriptions sometimes include plausible-sounding but incorrect details (hallucinations). The developer wants to ensure the model's responses are strictly based on the provided product data and does not add any external or invented information. Which approach should the developer use?

Question 43hardmultiple choice

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A developer uses Azure OpenAI Service to generate data transformation scripts. The generated scripts sometimes contain logical errors. To make the model's output more deterministic and reduce variability, which parameter should the developer decrease?

Question 44mediummultiple choice

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A company uses Azure OpenAI Service to generate marketing copy. They notice that sometimes the generated text contains repetitive phrases or gets stuck in loops. They want to reduce this behavior without changing the overall creativity of the model. Which parameter should they adjust?

Question 45mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate ad copy. They notice the model sometimes uses offensive language. Which Azure OpenAI feature should they use to automatically block such content?

Question 46mediummultiple choice

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A developer uses Azure OpenAI Service to generate conversation scripts for a chatbot. The developer wants to encourage the model to introduce new topics and avoid repeatedly discussing the same subject matter. Which parameter should the developer increase?

Question 47hardmultiple choice

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A marketing team wants to use AI to automatically create new product descriptions that are original and varied, simulating human-like writing. Which type of AI model is best suited for this task?

Question 48mediummultiple choice

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A fashion retailer wants to automatically generate new, unique images of clothing items based on textual descriptions (e.g., 'a blue silk dress with floral patterns'). Which Azure service would be most appropriate to accomplish this?

Question 49mediummultiple choice

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A company uses a generative AI model to answer customer questions about their products. They observe that the model sometimes produces factually incorrect or fabricated information. To reduce these inaccuracies, they want to provide the model with relevant, up-to-date product documentation as context before generating a response. Which technique is being applied?

Question 50hardmultiple choice

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A company uses a GPT-based model to generate marketing copy. They notice the model occasionally produces text that includes harmful stereotypes. They want to reduce these harmful outputs without retraining the model. Which approach is most appropriate?

Question 51mediummultiple choice

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A company uses a large language model to generate answers to employee questions about internal HR policies. However, the model sometimes produces answers that are factually incorrect or not based on the official policies. To reduce these inaccuracies, the company wants to provide the model with relevant, up-to-date policy documents as extra context before generating a response. Which technique is being applied?

Question 52hardmultiple choice

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A company uses a generative AI model to create blog posts. They want to ensure that the model's output never contains offensive or harmful language before the content is published. They implement a system that checks the generated text against a list of prohibited terms and blocks or edits the content if necessary. Which type of safety measure is this?

Question 53mediummultiple choice

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A marketing team wants to use a generative AI model to produce social media posts that match their brand's specific tone and style. They have a small set of example posts written by their copywriters. Which approach should they use to customize the model's outputs without retraining the entire model?

Question 54easymultiple choice

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A digital marketing agency wants to use an AI model that can create original images of products in different styles based on text prompts, such as 'a luxury watch in a futuristic setting.' Which Azure service should they choose?

Question 55easymultiple choice

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A company wants to build a chatbot that can engage in free-form conversations with customers, answering questions and providing information without being limited to a fixed set of responses. Which type of AI model is most suitable?

Question 56mediummultiple choice

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A company wants to build a chatbot that answers customer questions using a large language model. The company has an extensive internal knowledge base with accurate, up-to-date product information. To ensure the chatbot's answers are based on this reliable source rather than the model's internal knowledge, which technique should they use?

Question 57mediummultiple choice

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A museum wants to create an interactive exhibit where visitors can type a description of a fictional creature, such as 'a fire-breathing dragon with emerald scales and golden wings,' and the system generates an image of that creature in real time. The museum must ensure that the generated images are safe and appropriate for all ages, including children. Which Azure service should they use, and which safety feature should they configure?

Question 58mediummultiple choice

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A company wants to use Azure OpenAI Service to generate product descriptions. They need to ensure the model's output is based on their specific product catalog and pricing, not on generic information. Which approach should they use?

Question 59mediummultiple choice

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A company wants to use Azure OpenAI to generate personalized marketing emails. They have a large dataset of customer purchase histories. They want the model to generate emails that recommend products based on individual customer preferences without retraining the entire model. Which technique should they use?

Question 60mediummultiple choice

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A marketing agency wants to use Azure OpenAI Service to generate product descriptions. They need the descriptions to be factually accurate and based on their specific product catalog, which is stored in a vector database. Which technique should they use to ground the model's outputs in their own data?

Question 61mediummultiple choice

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A company uses Azure OpenAI Service to generate summaries of long technical documents. They notice that the model sometimes produces summaries that sound plausible but contain factual errors contradicting the source document. Which concept describes this type of error in large language models?

Question 62easymultiple choice

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A developer wants to use Azure OpenAI to build a customer service chatbot that can answer questions about a company's return policy. They create a set of example question-answer pairs in the prompt without retraining the model. Which technique is being used?

Question 63mediummultiple choice

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A marketing team uses Azure OpenAI to generate product descriptions. They want the output to reflect their latest catalog and current pricing, not the model's general knowledge. Which technique should they use?

Question 64hardmultiple choice

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A company uses Azure OpenAI Service to generate marketing copy for a new product. They have a strict brand voice that requires formal, technical language and explicitly prohibits any humorous or informal phrases. They want to enforce these constraints without retraining the model. Which technique should they use?

Question 65mediummultiple choice

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

Question 66mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate product descriptions. They have a base description and want the model to produce multiple variations with different tones, such as formal, playful, and technical, while still being factually accurate. Which parameter should they adjust to control the randomness and diversity of the output?

Question 67mediummultiple choice

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A company uses Azure OpenAI Service to automatically generate customer support email responses. They want to ensure that the model does not produce responses containing offensive language, hate speech, or biased content. Which Microsoft responsible AI principle is most directly addressed by implementing content filters that screen the model's output before it is sent?

Question 68hardmultiple choice

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A writer uses Azure OpenAI Service to generate multiple story ideas. They find that the model often repeats the same concepts across different outputs. Which parameter should they increase to reduce repetition and encourage more novel content?

Question 69mediummultiple choice

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A company uses Azure OpenAI to generate marketing copy. They want to ensure that the generated text does not contain inappropriate or harmful content before it is published. Which Azure OpenAI feature is specifically designed for this purpose?

Question 70easymultiple choice

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A company wants to build a chatbot that answers customer questions using only their internal knowledge base, which consists of several PDFs and Word documents. They do not want the chatbot to use any information from the model's pre-trained knowledge. Which Azure OpenAI feature should they use to achieve this?

Question 71mediummultiple choice

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A company wants to use Azure OpenAI to generate realistic customer conversations for training a chatbot. They have a set of example conversation snippets and want the model to mimic the style and structure of those examples. The company does not want to retrain the model. Which approach should they use?

Question 72easymultiple choice

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A marketing team uses Azure OpenAI to generate social media posts. They want to ensure the generated text maintains a consistent, predictable brand voice without being overly creative or random. Which parameter should they primarily adjust to control the randomness of the output?

Question 73mediummultiple choice

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A company wants to use Azure OpenAI to generate product descriptions. They have a few example descriptions that perfectly match their desired style and structure. They want the model to produce new descriptions in the same style without retraining the underlying model. Which approach should they use?

Question 74mediummultiple choice

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A developer uses Azure OpenAI Service to generate code. They provide a few examples of function definitions and their corresponding descriptions, then ask the model to write a new function based on a new description. Which technique is the developer using?

Question 75mediummultiple choice

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A marketing team wants to use Azure OpenAI to generate blog post outlines. They have a single example of an outline that follows their preferred structure: introduction, three key points, conclusion. They want the model to generate new outlines that follow the same structure without retraining the model. Which technique should they use?

Question 76easymultiple choice

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A customer service company uses Azure OpenAI Service to generate automated replies to customer inquiries. They want each reply to adopt a polite and empathetic tone. Which configuration should they use to guide the model's behavior without retraining?

Question 77mediummultiple choice

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A developer is using Azure OpenAI Service to generate structured data in JSON format. They want to ensure that every response is valid JSON without adding instructions in every prompt. Which Azure OpenAI feature should they configure?

Question 78mediummultiple choice

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A content creator uses Azure OpenAI to generate unique story ideas for a fantasy novel. They want the output to be highly creative and unpredictable, avoiding common clichés. Which parameter should they primarily increase to achieve this?

Question 79mediummultiple choice

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An advertising agency wants to generate product images from text prompts. They need the ability to specify the visual style (e.g., photorealistic, oil painting) and also ensure that the generated images are safe for work by blocking inappropriate content. Which Azure OpenAI model and feature should they use?

Question 80mediummultiple choice

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A company uses Azure OpenAI Service to generate marketing copy. They want to ensure that the generated text does not contain offensive language or harmful stereotypes, even if the prompt inadvertently leads the model in that direction. Which Azure OpenAI feature should they configure to help prevent such outputs?

Question 81mediummultiple choice

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A developer is using Azure OpenAI to generate code snippets for a banking application. The developer wants to minimize the risk that the generated code contains security vulnerabilities or malicious instructions, even if the prompt is ambiguous. Which Azure OpenAI feature should the developer configure to address this concern?

Question 82mediummultiple choice

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A developer uses Azure OpenAI to generate product descriptions. They provide five examples of product descriptions that follow a specific format (name, features, price, call to action). They then ask the model to write a new description for a given product, expecting the same format. Which technique is the developer using?

Question 83mediummultiple choice

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A creative agency wants to use Azure OpenAI to generate marketing images from text descriptions. They need to ensure that the generated images are appropriate for all audiences by automatically blocking sexually explicit or violent content. Which Azure OpenAI feature should they configure to meet this requirement?

Question 84mediummultiple choice

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A legal firm wants to use Azure OpenAI to generate summaries of lengthy contracts. The firm requires that the generated summaries are strictly based on the provided contract text and do not include any external knowledge or hallucinated facts. Which Azure OpenAI feature should the firm configure to meet this requirement?

Question 85mediummultiple choice

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A marketing team uses Azure OpenAI Service to generate product descriptions. They want the descriptions to follow a specific brand voice (formal, concise) and avoid generating any harmful or offensive language. Which combination of features should the team use?

Question 86easymultiple choice

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A developer wants to use Azure OpenAI to generate text that follows a specific style, such as formal business letters. They provide three examples of the desired output format in the prompt and then ask the model to generate a new letter. Which technique is the developer using?

Question 87easymultiple choice

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A marketing team wants to use Azure OpenAI to generate blog posts. They require the output to avoid toxic language and adhere to their brand safety guidelines. Which Azure OpenAI feature should they configure to automatically block harmful content?

Question 88mediummultiple choice

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A creative agency wants to use Azure OpenAI to generate unique images for social media campaigns based on text descriptions. Which Azure OpenAI model should they use for this purpose?

Question 89mediummultiple choice

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A software company uses Azure OpenAI to generate code snippets. They want to evaluate how confident the model is in each token it generates. Which Azure OpenAI feature provides a numerical measure of confidence for each generated token?

Question 90mediummultiple choice

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A developer uses Azure OpenAI to generate Python code. They want the model to limit the length of the generated code to avoid overly long and complex functions. Which parameter should the developer set in the API call?

Question 91hardmultiple choice

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A company uses Azure OpenAI to build a customer service chatbot. They want to prevent malicious users from injecting prompts that cause the chatbot to behave unexpectedly, such as revealing its system instructions. Which responsible AI consideration is most directly relevant?

Question 92hardmultiple choice

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A developer is using Azure OpenAI to generate creative product descriptions. The outputs are often repetitive and lack variety. The developer wants to increase the diversity of the generated text while still keeping it coherent. Which parameter should the developer increase?

Question 93mediummultiple choice

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A developer uses Azure OpenAI to generate marketing copy. They want the model to follow a very specific tone and style. They provide a few high-quality examples of desired output before the actual prompt. Which technique is the developer using?

Question 94mediummultiple choice

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A company wants to build a chatbot that can answer questions based on its internal policy documents. The documents are stored in Azure Blob Storage. They plan to use Azure OpenAI to generate answers. Which approach should they use to ensure the answers are grounded in the actual policy content?

Question 95hardmultiple choice

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A developer uses Azure OpenAI to generate Python code snippets. They want to prevent the model from producing overly long and complex functions by setting a maximum length for the generated output. Which parameter should the developer set in the API call?

Question 96mediummultiple choice

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A developer uses Azure OpenAI to generate customer support responses. The developer wants to ensure that the model does not produce responses that contain offensive, hateful, or harmful language, even when users input problematic prompts. Which Azure OpenAI feature should the developer configure to achieve this?

Question 97hardmultiple choice

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A developer is building a customer support chatbot using Azure OpenAI. The chatbot should never reveal its system instructions or internal configuration. The developer wants to add a rule at the beginning of the conversation to prevent prompt injection attacks. Which technique should they use?

Question 98hardmultiple choice

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A developer is using Azure OpenAI to generate Python code snippets. They notice that the generated code often contains syntax errors because the model introduces too much randomness. Which parameter should the developer decrease to make the output more deterministic and reduce syntax errors?

Question 99mediummultiple choice

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A developer uses Azure OpenAI to generate product descriptions. The outputs often repeat the same phrases multiple times within a single description. Which parameter should the developer increase to reduce this repetition?

Question 100hardmultiple choice

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A developer is using Azure OpenAI with GPT-4 to build a chatbot that answers legal questions based on a company's internal policy documents. The developer wants the model's responses to be maximally deterministic and factual, avoiding any creative or speculative language. Which parameter should the developer set to the lowest possible value in the API call?

Question 101easymultiple choice

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What is generative AI?

Question 102mediummultiple choice

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What is a large language model (LLM)?

Question 103mediummultiple choice

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What is a prompt in the context of generative AI?

Question 104easymultiple choice

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What is Azure OpenAI Service?

Question 105mediummultiple choice

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What is prompt engineering?

Question 106mediummultiple choice

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What is grounding in the context of generative AI and Retrieval Augmented Generation (RAG)?

Question 107mediummultiple choice

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What is a 'hallucination' in the context of large language models?

Question 108mediummultiple choice

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What is a copilot in the context of Microsoft AI products?

Question 109mediummultiple choice

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What is a system prompt in an Azure OpenAI deployment?

Question 110easymultiple choice

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What is the primary difference between GPT models and DALL-E models from OpenAI?

Question 111mediummultiple choice

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What is 'temperature' in the context of generative AI model parameters?

Question 112mediummultiple choice

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What is fine-tuning in the context of large language models?

Question 113easymultiple choice

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What is the context window in a large language model?

Question 114mediummultiple choice

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What is Azure AI Studio?

Question 115mediummultiple choice

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What are embeddings in the context of AI and language models?

Question 116mediummultiple choice

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What is the difference between Azure OpenAI Service and the public OpenAI API?

Question 117easymultiple choice

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What is the primary use case for DALL-E models available in Azure OpenAI?

Question 118mediummultiple choice

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What is a foundation model in the context of AI?

Question 119mediummultiple choice

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What is the purpose of Azure AI Content Safety in the context of generative AI deployments?

Question 120easymultiple choice

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What is the maximum output length parameter 'max tokens' used for in Azure OpenAI?

Question 121mediummultiple choice

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What is the difference between zero-shot, one-shot, and few-shot learning in prompting?

Question 122mediummultiple choice

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What is Azure AI Search (formerly Cognitive Search) and how does it relate to generative AI?

Question 123mediummultiple choice

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What are 'guardrails' in the context of responsible generative AI deployment?

Question 124mediummultiple choice

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What is 'responsible AI by design' in the context of building Azure AI applications?

Question 125easymultiple choice

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What is the role of the Azure AI Foundry (AI Studio) playground?

Question 126mediummultiple choice

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What is the primary benefit of using Retrieval Augmented Generation (RAG) over relying solely on an LLM's trained knowledge?

Question 127mediummultiple choice

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What is the purpose of system messages in Azure OpenAI API calls?

Question 128mediummultiple choice

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What is a vector database and why is it important for generative AI applications?

Question 129easymultiple choice

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What is the Whisper model available in Azure OpenAI used for?

Question 130mediummultiple choice

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What is the purpose of 'top_p' (nucleus sampling) in Azure OpenAI API calls?

Question 131mediummultiple choice

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What is 'chain of thought' prompting in generative AI?

Question 132easymultiple choice

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What does the Azure AI Foundry model catalog provide?

Question 133mediummultiple choice

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What is the Azure OpenAI 'content filter' and what categories of content does it cover?

Question 134mediummultiple choice

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What is 'grounding with Bing search' in Microsoft Copilot?

Question 135mediummultiple choice

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What is an AI agent in the context of Azure AI and generative AI?

Question 136mediummultiple choice

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What is 'semantic kernel' in Microsoft's AI development ecosystem?

Question 137easymultiple choice

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What is Microsoft 365 Copilot and how does it use generative AI?

Question 138mediummultiple choice

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What is the 'phi' family of models in Azure AI and what makes them distinctive?

Question 139mediummultiple choice

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What is the 'frequency penalty' parameter in Azure OpenAI API calls?

Question 140mediummultiple choice

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What are 'plugins' or 'tools' in the context of AI agents and Microsoft Copilot?

Question 141mediummultiple choice

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What is the Azure AI Evaluation SDK used for in generative AI development?

Question 142mediummultiple choice

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What is 'tool calling' (function calling) in Azure OpenAI?

Question 143easymultiple choice

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What is the GPT-4o model in Azure OpenAI?

Question 144mediummultiple choice

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What is 'Azure AI Foundry' and what is its primary purpose?

Question 145mediummultiple choice

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What is 'model deployment' in Azure OpenAI, and why are named deployments used?

Question 146easymultiple choice

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What is GitHub Copilot and how does it use AI?

Question 147mediummultiple choice

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What is the 'presence penalty' parameter in Azure OpenAI API calls?

Question 148mediummultiple choice

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What is 'retrieval augmented generation' (RAG) and which Azure services typically implement it?

Question 149mediummultiple choice

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What is 'grounding' in the context of Azure OpenAI and Retrieval-Augmented Generation?

Question 150easymultiple choice

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What is a 'system message' (system prompt) in Azure OpenAI chat models?

Question 151mediummultiple choice

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What is 'content moderation' in the context of Azure OpenAI?

Question 152hardmultiple choice

Read the full NAT/PAT explanation →

What is 'hallucination' in large language models and what techniques help reduce it?

Question 153mediummultiple choice

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What is 'semantic search' in Azure AI Search (cognitive search)?

Question 154easymultiple choice

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What is the 'Azure OpenAI Playground' and what is it used for?

Question 155mediummultiple choice

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What is 'prompt injection' and why is it a security concern for AI applications?

Question 156easymultiple choice

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What is 'DALL-E' in Azure OpenAI and what does it do?

Question 157mediummultiple choice

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What is 'few-shot prompting' and how does it improve model outputs?

Question 158hardmultiple choice

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What is 'chain-of-thought prompting' and when is it most effective?

Question 159easymultiple choice

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What are 'embeddings' in Azure OpenAI and what are they used for?

Question 160mediummultiple choice

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What is 'Azure AI Studio' and what can you do with it?

Question 161mediummultiple choice

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What is 'Azure AI Content Safety' and what types of harmful content does it detect?

Question 162easymultiple choice

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What is 'fine-tuning' a language model and when should you use it instead of prompt engineering?

Question 163mediummultiple choice

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What is the 'model catalogue' in Azure AI Foundry/AI Studio?

Question 164hardmultiple choice

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What is 'constitutional AI' and how does it relate to responsible AI development?

Question 165mediummultiple choice

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What is 'Azure OpenAI's Assistants API' and what capabilities does it add?

Question 166easymultiple choice

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What is 'Copilot' in Microsoft's AI strategy and how does it relate to Azure OpenAI?

Question 167mediummultiple choice

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What is 'prompt flow' in Azure AI Foundry?

Question 168mediummultiple choice

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What is 'evaluation' of generative AI models in Azure AI Foundry?

Question 169mediummultiple choice

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What is 'zero-shot prompting' and how does it work?

Question 170mediummultiple choice

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What is 'retrieval-augmented generation' (RAG) and what problem does it solve?

Question 171easymultiple choice

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What is 'text generation' as a generative AI capability and what are common use cases?

Question 172mediummultiple choice

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What is 'structured output' (JSON mode) in Azure OpenAI?

Question 173mediummultiple choice

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What is 'Azure OpenAI's batch API' and when should you use it?

Question 174hardmultiple choice

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What is 'agentic AI' and how does it differ from a simple chatbot?

Question 175easymultiple choice

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What is the 'Phi' family of models in Azure AI Foundry and what makes them distinctive?

Question 176mediummultiple choice

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What is 'Microsoft Copilot Studio' and what is it used for?

Question 177mediummultiple choice

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What is 'Whisper' in Azure OpenAI and what can it do?

Question 178mediummultiple choice

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What is 'multi-agent systems' in the context of Azure AI and agentic workflows?

Question 179easymultiple choice

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What is 'code generation' as a generative AI capability and how is it used in development?

Question 180mediummultiple choice

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What is 'temperature' parameter in Azure OpenAI and how does it affect output?

Question 181mediummultiple choice

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What is 'token pricing' in Azure OpenAI and what counts as a token?

Question 182mediummultiple choice

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What is 'Azure AI Search' (formerly Cognitive Search) and how does it support generative AI?

Question 183hardmultiple choice

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What is 'model distillation' and why might you distill a large model to a small one?

Question 184mediummultiple choice

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What is 'top_p' (nucleus sampling) in Azure OpenAI and how does it differ from temperature?

Question 185easymultiple choice

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What is 'max_tokens' parameter in Azure OpenAI and how does it affect responses?

Question 186mediummultiple choice

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What is 'Azure OpenAI on your data' and what does it enable?

Question 187mediummultiple choice

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What is 'Microsoft Semantic Kernel' and how does it relate to Azure OpenAI?

Question 188hardmultiple choice

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What is 'speculative decoding' and how does it improve LLM inference speed?

Question 189mediummultiple choice

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What is 'Azure OpenAI's fine-tuning' feature and what data format does it require?

Question 190mediummultiple choice

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What is 'Microsoft 365 Copilot' and how does it use Azure OpenAI?

Question 191mediummultiple choice

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What is 'responsible AI impact assessment' for generative AI applications?

Question 192mediummultiple choice

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What is 'Azure OpenAI deployment' and how does it differ from a 'model'?

Question 193easymultiple choice

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What is 'GitHub Copilot' and how does it relate to Azure OpenAI?

Question 194mediummultiple choice

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What is 'context length' limitation in LLMs and how do 'long-context models' address it?

Question 195mediummultiple choice

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What is 'Azure AI Foundry's model benchmarks' and how do they help you choose a model?

Question 196mediummultiple choice

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What is 'Azure AI Services multi-service resource' and what is its advantage?

Question 197easymultiple choice

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What is 'Azure AI Content Safety Studio' and what does it help you do?

Question 198mediummultiple choice

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What is 'Azure OpenAI's content filter' configurability and why does it matter?

Question 199mediummultiple choice

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What is 'citation' in generative AI and why is it important for trust?

Question 200mediummultiple choice

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

Question 201hardmultiple choice

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What is 'mixture of experts' (MoE) architecture and how does it relate to efficient LLMs?

Question 202mediummultiple choice

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What is 'guardrails' in generative AI applications and how are they implemented?

Question 203mediumdrag order

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Drag and drop the steps to perform a face detection using Azure Face API into the correct order.

Drag steps to the numbered slots on the right, or tap a step then tap a slot.

Steps

Order

1Step 1

2Step 2

3Step 3

4Step 4

5Step 5

Question 204mediumdrag order

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Drag and drop the steps to implement content moderation using Azure Content Moderator into the correct order.

Drag steps to the numbered slots on the right, or tap a step then tap a slot.

Steps

Order

1Step 1

2Step 2

3Step 3

4Step 4

5Step 5

Question 205mediummatching

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Match each Azure AI workload to its responsible AI principle.

Drag a concept onto its matching description — or click a concept then click the description.

Concepts

Matches

Privacy and security

Fairness

Reliability and safety

Transparency

Accountability

Question 206mediummatching

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Match each Azure AI service to its data input type.

Drag a concept onto its matching description — or click a concept then click the description.

Concepts

Matches

Image URL or binary

Audio file or stream

Text strings

Document files (PDF, image)