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Updated: Sep 16, 2026
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How to Prepare For AI-102: Designing and Implementing an Azure AI Solution Exam
Preparation Guide for AI-102: Designing and Implementing an Azure AI Solution Exam
Introduction
Microsoft has created a track for Azure professionals analyze the requirements for AI solutions, recommend appropriate tools and technologies, and implements solutions that meet scalability and performance requirements, to get certified this platform. solution architects translate the vision and work with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end solutions. The assessment is based on a rigorous exam using industry standard methodology to determine whether a candidate meets Microsoft's proficiency standards.
This certification been actually designed for aspirants design and implement AI apps and agents that use Microsoft Azure Cognitive Services.
For this exam candidate having proficiency in using cognitive service APIs to meet business requirements, appropriate AI models and services, automation requirements, data privacy and protection , bot state data , cognitive service output would be an added advantage.
Certification is evidence of your skills, expertise in those areas in which you like to work. If candidate wants to work as AI solution architect and prove his knowledge, certification offered by Microsoft. This AI-102 Exam Certification helps a candidate to validates his skills in Azure platform.
In this guide, we will cover the AI-102: Designing and Implementing an Azure AI Solution Certification exam, AI-102: Designing and Implementing an Azure AI Solution Certified professional salary and all aspects of the AI-102: Designing and Implementing an Azure AI Solution Certification.
Difficulty in Writing AI-102: Designing and Implementing an Azure AI Solution Exam
AI-102: Designing and Implementing an Azure AI Solution is a privileged achievement one could be graced with. But adverse to general notion certifying with Microsoft is not that challenging if the candidates have proper preparation material to pass the AI-102: Designing and Implementing an Azure AI Solution exam with good grades. Questions answers and clarifications which are designed in form of Exam4Labs exam dumps make sure to cover entire course content. Exam4Labs have a brilliant AI-102: Designing and Implementing an Azure AI Solution exam dumps with most recent and important questions and answers in PDF files. Exam4Labs is sure about the exactness and legitimacy of AI-102: Designing and Implementing an Azure AI Solution exam dumps and in this manner. Candidates can easily pass the AI-102: Designing and Implementing an Azure AI Solution exam with genuine AI-102: Designing and Implementing an Azure AI Solution exam dumps and get MICROSOFT certification. These exam dumps are viewed as the best source to understand the AI-102: Designing and Implementing an Azure AI Solution well by simply pursuing examples questions and answers. If candidate completes practice the exam with certification AI-102 exam dumps along with self-assessment to get the proper idea on MICROSOFT accreditation and to ace the certification exam.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102 Korean Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Exam Duration: | 100 minutes |
| Passing Score: | 700 (scaled score out of 1000) |
| Certificate Validity Period: | 1 year (renewable via free online assessment) |
| Real Exam Qty: | 40-60 |
| Exam Price: | $165 USD (varies by region: £113 GBP, €126 EUR) |
| Exam Format: | Multiple choice, Case studies, Multiple select, Drag-and-drop, Performance-based scenarios, Hot area |
| Related Certifications: | Microsoft Certified: Azure Data Scientist Associate Microsoft Certified: Azure AI Fundamentals (AI-900) Microsoft Certified: Azure Developer Associate |
| Available Languages: | Italian, Spanish, Japanese, Portuguese (Brazil), Indonesian, Korean, Chinese (Simplified), Arabic (Saudi Arabia), English, German, French |
| Recommended Training: | Microsoft Learn Learning Paths for AI-102 AI-102T00: Designing and Implementing a Microsoft Azure AI Solution |
| Exam Registration: | Pearson VUE Scheduling Microsoft Certification Exam Registration |
| Sample Questions: | Microsoft AI-102 Korean Sample Questions |
| Exam Way: | Online proctored (OnVUE) or onsite at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; recommended: experience with Azure services, AI concepts, and proficiency in Python or C#; AI-900 certification is recommended but not required |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-102 |
Topics Covered
Exam AI-102 contains five topics each of which is intended to check specific skills.
1. Plan and Manage an Azure Cognitive Services Solution
This topic implies your ability to choose the suitable Cognitive Services resource, create it, plan and design security for a Cognitive Services solution, and apply Cognitive Services containers. This means that you should be competent in selecting the appropriate cognitive service for solutions that refer to language analysis, speech, decision support, and vision. You also should possess skills to operate costs of Cognitive Services, create a Cognitive Services resource, and monitor a cognitive service. This part also checks how well you can operate Cognitive Services account keys, and protect Cognitive Services. Your knowledge of using Face API, Computer Vision, Speech, Text Analysis, and ability to integrate Cognitive Services Containers in Microsoft Azure will also be assessed.
2. Implement Computer Vision Solutions
The second topic is designed to check your skills in using the Computer Vision API to get image descriptions, define landmarks, find brands, edit content in images, and create thumbnails. In this part, you are expected to be able to detect faces and recognize them in images, analyze facial features, and match similar faces with the help of the Face API. Being competent in utilizing the Custom Vision service, you should demonstrate your skills in applying image classification and implementing an object detection solution. Besides, your ability to analyze video by implementing Azure Video Analyzer for Media will be measured.
3. Implement Natural Language Processing Solutions
In the third topic, candidates are required to show their skills in analyzing text by utilizing the Text Analytics service, control speech by implementing the Speech service, translate the text with the help of the Translator service. This domain also checks your proficiency in creating and optimizing an initial language model by utilizing LUIS, and finally, managing it.
4. Implement Knowledge Mining Solutions
In this domain, you will be required to have expertise related to applying a Cognitive Search solution, which implies creating data sources, identifying an index, running an indexer, and using synonyms. This topic also aims to evaluate your ability to apply an enrichment pipeline, use a knowledge store, operate a Cognitive Search solution and indexing.
5. Implement Conversational AI Solutions
This domain will evaluate your capacity in utilizing QnA Maker to make a knowledge base, creating and implementing conversation flow, creating a bot by utilizing either the Bot Framework Composer or the Bot Framework SDK. Finally, you will need to demonstrate your skills in integrating Cognitive Services into a bot.
Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Build and deploy custom vision models - Extract text and handwriting from images - Integrate vision capabilities into applications - Analyze images and detect objects/features - Process and index video content |
| Topic 2: Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Deploy and manage generative models - Orchestrate multiple models and containers - Implement model monitoring and feedback |
| Topic 3: Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Develop multi-agent workflows and orchestration - Test, deploy, and optimize agents |
| Topic 4: Implement natural language processing solutions | 15-20% | - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots - Customize and deploy NLP models - Implement translation and summarization |
| Topic 5: Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes |
| Topic 6: Plan and manage an Azure AI solution | 20-25% | - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select appropriate Microsoft Foundry Services - Monitor, optimize, and secure AI solutions - Select suitable AI models - Create and configure Azure AI resources - Plan solutions aligned with responsible AI principles |
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