Microsoft AI-102 Study Material

Microsoft AI-102 Exam Study Material

Designing and Implementing a Microsoft Azure AI Solution
  • 423 Questions & Answers
  • Update Date : July 13, 2026

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Question 1

Select the answer that correctly completes the sentence.

Question 2

You have a product support manual. You need to build a product support chatbot based on the manual. The solution must minimize development effort and costs. What should you use?

A. Azure Al Phi-3-medium with fine-tuning 
B. Azure A1 Language Custom question answering 
C. Azure OpenA1 GPI-4 with grounding data that uses Azure Al Search 
D. Azure Al Document Intelligence 

Question 3

You have an Azure subscription. The subscription contains an Azure OpenAI resource that hosts a GPT-3.5 Turbo model named Model1. You configure Model1 to use the following system message: "You are an Al assistant that helps people solve mathematical puzzles. Explain your answers as if the request is by a 4- year-old." Which type of prompt engineering technique is this an example of?

A. few-shot learning 
B. affordance 
C. chain of thought 
D. priming 

Question 4

You are building an app that uses a Language Understanding model to analyze text files. You need to ensure that the app can detect the following entities: • Temperatures • Currency values • Email addresses • Telephone numbers The solution must minimize development effort. Which model capability should you use?

A. list entities 
B. learned entities 
C. utterances 
D. regular expression components 
E. pre-built entity components 

Question 5

You have a training dataset that contains 10,000 PDF documents. The documents contain scanned books, comics, and magazines. You are building a solution that will use Azure Al and a custom model. You need to train the model by using Language Studio. The solution must meet the following requirements: • Tag each item as a book, comic, or magazine. • Minimize development effort. What should you use?

A. a custom extraction model 
B. a multi label classification project 
C. a custom named entity recognition (NER) project 
D. a multi label image classification model 

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