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*** Course has been updated as per the latest official exam update of 30th April, 2025 ***NOTE: Most of the code samples in the course are in C#.Welcome to the Azure AI Engineer Associate AI-102 - Practice Test Course!Are you preparing for the Azure AI Engineer Associate (AI-102) certification exam? This course is designed to help you succeed by providing high-quality practice tests that closely mirror the real exam.What You'll Get:350+ Latest exam questions with detailed explanations to each answer (includes case study questions)Realistic Exam Simulation: My practice tests are designed to reflect the format, style, and difficulty of the official Azure AI Engineer Associate exam. This ensures you get a realistic testing experience.Comprehensive Coverage: The practice tests cover all the domains and objectives of the AI-102 exam, including:Plan and manage an Azure AI solutionImplement generative AI solutionsImplement an agentic solutionImplement computer vision solutionsImplement natural language processing solutionsImplement knowledge mining and information extraction solutionsDetailed Explanations: Each question comes with a detailed explanation to help you understand the concepts and reasoning behind the correct answers. This is crucial for deepening your knowledge and ensuring you're fully prepared. For each question, I have explained why an answer is correct and have also explained why other options are incorrect. You will also find supporting reference links for a quick read.Variety of Questions: You'll find a mix of multiple-choice, multiple-response, and scenario-based questions to fully prepare you for what to expect on exam day.Performance Tracking: Keep track of your progress with the test review feature. Identify your strengths and areas for improvement to focus your study efforts effectively.Sneak peak into what you will get inside the course:Q1. You collect IoT sensor data from 100 industrial machines for a year. Each machine has 50 different sensors that generate data at one-minute intervals. In total, you have 5,000 time series datasets. You need to identify unusual values in each time series to help predict machinery failures. Which Azure service should you use?Azure AI Computer VisionAzure AI SearchAzure AI Document IntelligenceAzure AI Anomaly DetectorAnswer(s):Azure AI Anomaly Detector is CORRECT because it is specifically designed to detect anomalies in time series data. It uses advanced machine learning models to identify unexpected patterns or behaviors in data, which is essential for predictive maintenance. With the ability to analyze and detect irregularities across multiple time series datasets, this service is ideal for monitoring IoT sensor data to predict machinery failures.Azure AI Computer Vision is INCORRECT because this service is primarily focused on analyzing images and extracting information from visual data. It does not have the capabilities to handle time series data or detect anomalies in sensor readings.Azure AI Search is INCORRECT because it is a search-as-a-service solution that provides indexing and querying capabilities for various types of content, such as documents and databases. It is not designed for time series data analysis or anomaly detection.Azure AI Document Intelligence is INCORRECT because it focuses on extracting structured information from unstructured documents, such as forms and receipts. It does not have the functionality to analyze time series data for anomalies.***Q2. You have an Azure OpenAI resource named AI1 that hosts three deployments of the GPT 3.5 model. Each deployment is optimized for a unique workload. You plan to deploy three apps. Each app will access AI1 by using the REST API and will use the deployment that was optimized for the app's intended workload. You need to provide each app with access to AI1 and the appropriate deployment. The solution must ensure that only the apps can access AI1. What should you use to provide access to AI1?An API keyA bearer tokenA shared access signature (SAS) tokenAnswer(s):An API key is CORRECT because it is a common method for authenticating applications when accessing APIs, including Azure OpenAI services. API keys are straightforward to use and provide the necessary authentication to ensure that only authorized applications can access the specific deployments optimized for their intended workloads.A bearer token is INCORRECT because bearer tokens are typically used for authentication in OAuth 2.0 frameworks, which involves a more complex process including obtaining tokens from an authorization server. This is not as straightforward as using API keys for the given requirement.A shared access signature (SAS) token is INCORRECT because SAS tokens are primarily used to grant limited access to Azure Storage resources. They are not designed for authenticating access to Azure OpenAI resources via REST API.***Q3. You have an app named App1 that uses a custom Azure AI Document Intelligence model to recognize contract documents. You need to ensure that the model supports an additional contract format. The solution must minimize development effort. What should you do?Lower the confidence score threshold of App1.Create a new training set and add the additional contract format to the new training set. Create and train a new custom model.Add the additional contract format to the existing training set. Retrain the model.Lower the accuracy threshold of App1.Answer(s):Add the additional contract format to the existing training set. Retrain the model is CORRECT. This approach directly addresses the need to support an additional contract format without starting from scratch. By adding examples of the new contract format to the existing training set and retraining the model, you enhance the model's ability to recognize the new format while leveraging the already trained capabilities for existing formats. This minimizes development effort compared to creating and training a completely new model.Lower the confidence score threshold of App1 is INCORRECT because lowering the confidence score threshold might allow the model to recognize more documents as contracts, but it won't improve the model's ability to accurately recognize the new contract format. It could also increase the likelihood of false positives.Create a new training set and add the additional contract format to the new training set. Create and train a new custom model is INCORRECT because creating a new custom model from scratch is more labor-intensive and time-consuming than updating and retraining the existing model with additional data.Lower the accuracy threshold of App1 is INCORRECT because lowering the accuracy threshold does not enhance the model's ability to correctly identify and process the new contract format. It simply reduces the criteria for what is considered a successful match, which could lead to inaccurate results.

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