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To be eligible for AI-102 exam, candidates must have a fundamental understanding of Azure services, including Azure storage, compute, networking, and security. They should also have experience with data science concepts and machine learning models. The AI-102 exam is intended for professionals who work as AI engineers, data scientists, or developers who want to enhance their expertise in AI and Azure. Passing AI-102 exam validates their skills in designing and implementing end-to-end AI solutions that can leverage Azure AI services and tools.
The Microsoft AI-102 exam covers a wide range of topics, including natural language processing, computer vision, and speech recognition. Candidates are required to have a thorough understanding of Azure Cognitive Services, Bot Services, and Azure Machine Learning. They must also be able to design and implement AI solutions that are scalable, secure, and reliable.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Microsoft AI-102 (Designing and Implementing a Microsoft Azure AI Solution) exam is designed for individuals who want to test their skills and knowledge in designing and implementing AI solutions using Microsoft Azure. AI-102 exam tests the candidate's ability to design and implement AI algorithms, machine learning models, natural language processing solutions, and computer vision solutions on the Microsoft Azure platform. Candidates are expected to have a good understanding of Azure services and tools for AI, including Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service.
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Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement natural language processing solutions | 15-20% | - Customize and deploy NLP models - Build conversational AI and chatbots - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection |
| Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Deploy and manage generative models - Orchestrate multiple models and containers |
| Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Monitor, optimize, and secure AI solutions - Plan solutions aligned with responsible AI principles - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Create and configure Azure AI resources - Select suitable AI models |
| Implement knowledge mining and information extraction solutions | 15-20% | - Build knowledge bases and search indexes - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data |
| Implement computer vision solutions | 10-15% | - Extract text and handwriting from images - Integrate vision capabilities into applications - Analyze images and detect objects/features - Process and index video content - Build and deploy custom vision models |
| Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Develop multi-agent workflows and orchestration - Understand agent use cases and types - Test, deploy, and optimize agents |
Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions:
You are developing the shopping on-the-go project.
You need to build the Adaptive Card for the chatbot.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Comprehensive Detailed Explanation
The requirement is to build an Adaptive Card for the chatbot that supports multilingual product display and meets accessibility requirements.
Product Name Display
The product JSON stores localized names like " name " : { " en " : " ... " , " es " : " ... " , " pt " : " ... " } .
To dynamically render based on the current language, you must use name[language].
This ensures the product name shown in the card adapts automatically to the user's preferred language.
Stock Level Warning
Business rules require warnings when stock is low or out of stock.
This means you display the stock warning only when stockLevel is not ' OK ' .
Therefore, the correct condition is:
" $when " : " ${stockLevel != ' OK ' } "
Image Alt Text for Accessibility
Accessibility requirements specify that all images must have alt text in English, Spanish, and Portuguese.
In the product JSON, " alttext " is also localized:
" altText " : { " en " : " Bicycle " , " es " : " Bicicleta " , " pt " : " Bicicleta " } To render the correct localized alt text dynamically, use image.altText[language].
Correct Selections:
First blank: name[language]
Second blank: " $when " : " ${stockLevel != ' OK ' } "
Third blank: image.altText[language]
Microsoft References
Adaptive Cards Templating
Adaptive Card $when property
Multilingual data in Azure Cognitive Search and Adaptive Cards
You are building an app that will share user images.
You need to configure the app to perform the following actions when a user uploads an image:
* Categorize the image as either a photograph or a drawing.
* Generate a caption for the image.
The solution must minimize development effort.
Which two services should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. image classification in Custom Vision
- B. object detection in Computer Vision
- C. image descriptions in Computer Vision
- D. content tags in Computer Vision
- E. image type detection in Computer Vison
Correct Answer: C,E 🗳️
Explanation: Only visible for Prep4King members. You can sign-up / login (it's free).
You are building an app that will share user images.
You need to configure the app to meet the following requirement's
* uploaded images must be scanned and any text must be extracted from the images.
* Extracted text must be analyzed for the presence of profane language.
* The solution must minimize development effort.
what should you use for each requirement? To answer, select the apocopate opinions in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Text Extraction: b) Computer Vision
Computer Vision is a service that can analyze images and extract text from them using optical character recognition (OCR) or read API1. OCR can detect and extract printed or handwritten text from images in various languages and formats, such as PDF, TIFF, or JPEG2. Read API can perform asynchronous batch processing of text from multiple images, and can also handle text in tables, mixed languages, and rotated text3.
Profane Language Detection: c) Content Moderator
Content Moderator is a service that can detect and filter out potentially offensive or unwanted content in text, images, and videos. For text, Content Moderator can identify profane or abusive language, personal data, and custom terms that you define. You can also use Content Moderator to review and moderate the content manually or automatically using workflows.
What is a characteristic of a non-relational database?
- A. full support for Transact-SGL
- B. a fixed schema
- C. self describing entities
Correct Answer: C 🗳️
Explanation: Only visible for Prep4King members. You can sign-up / login (it's free).
Which statement is an example of Data Manipulation Language (DML)?
- A. UPDATE
- B. DROP
- C. Revoke
- D. CREATE
Correct Answer: A 🗳️
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