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Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Implement natural language processing solutions15-20%- Customize and deploy NLP models
- Perform text analysis, sentiment detection, and language detection
- Implement translation and summarization
- Build conversational AI and chatbots
Implement knowledge mining and information extraction solutions15-20%- Ingest and process structured/unstructured data
- Implement intelligent search and retrieval
- Build knowledge bases and search indexes
- Extract entities, relationships, and key phrases
Implement computer vision solutions10-15%- Analyze images and detect objects/features
- Extract text and handwriting from images
- Process and index video content
- Integrate vision capabilities into applications
- Build and deploy custom vision models
Plan and manage an Azure AI solution20-25%- Select suitable AI models
- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
- Monitor, optimize, and secure AI solutions
- Select appropriate Microsoft Foundry Services
- Plan solutions aligned with responsible AI principles
- Create and configure Azure AI resources
Implement an agentic solution5-10%- Understand agent use cases and types
- Develop multi-agent workflows and orchestration
- Test, deploy, and optimize agents
- Build agents with Microsoft Foundry Agent Service
Implement generative AI solutions15-20%- Integrate Azure OpenAI and other generative models
- Apply prompt engineering and fine-tuning
- Orchestrate multiple models and containers
- Implement model monitoring and feedback
- Deploy and manage generative models

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Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q328-Q333):

NEW QUESTION # 328
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:


NEW QUESTION # 329
You are building a language learning solution.
You need to recommend which Azure services can be used to perform the following tasks:
* Analyze lesson plans submitted by teachers and extract key fields, such as lesson times and required texts.
* Analyze learning content and provide students with pictures that represent commonly used words or phrases in the text The solution must minimize development effort.
Which Azure service should you recommend for each task? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Analyze lesson plans and extract key fields
Use Azure AI Document Intelligence (Form Recognizer) to automatically extract structured data (dates/times, required texts, names, etc.) from uploaded lesson-plan documents (PDFs/images). It provides prebuilt and custom extraction with minimal code via Document Intelligence Studio.
Analyze learning content and show pictures for common words/phrases
Use Immersive Reader, which includes features like Picture Dictionary and text comprehension supports directly in apps with minimal development. It can highlight words and show illustrative images to aid vocabulary learning-exactly the requirement.
Other options are not a fit:
Azure AI Custom Vision is for training image classifiers/detectors, not text comprehension.
Azure AI Search indexes and searches content; it doesn't provide picture dictionary/reading experience.
Microsoft Azure AI References
Document Intelligence (Form Recognizer) overview & extraction capabilities: learn.microsoft.com/azure/ai- services/document-intelligence/overview Immersive Reader - Picture Dictionary & reading features: learn.microsoft.com/azure/ai-services/immersive- reader/overview


NEW QUESTION # 330
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You build a language model by using a Language Understanding service. The language model is used to search for information on a contact list by using an intent named FindContact.
A conversational expert provides you with the following list of phrases to use for training.
Find contacts in London.
Who do I know in Seattle? Search for contacts in Ukraine.
You need to implement the phrase list in Language Understanding.
Solution: You create a new entity for the domain.
Does this meet the goal?

Answer: B

Explanation:
Comprehensive Detailed Explanation
The scenario is identical to Question 43:
You have a FindContact intent.
Training phrases include city names (London, Seattle, Ukraine).
You must model location properly in Language Understanding.
Why the Proposed Solution is Wrong
The solution says: "Create a new entity for the domain."
Entities in LUIS/CLU represent specific data types to extract (e.g., location, date, contact name).
Domains in Language Understanding are prebuilt sets of intents and entities for common use cases (like Calendar, Home Automation, Communication).
Creating an "entity for the domain" is conceptually incorrect - entities are not meant to represent domains.
What we really need is to model location as an entity (for example, using the prebuilt GeographyV2 entity), not to create a generic "domain entity." Correct Approach Keep the FindContact intent.
Add a Location entity (prebuilt GeographyV2 or custom "Location").
Train the model so that London, Seattle, Ukraine are recognized as entity values within the FindContact intent.
Option Analysis
A). Yes # Incorrect. This would not meet the goal.
B). No # Correct. Creating a domain entity is not the right way; instead, a proper location entity should be added.
The Answer: B. No
Microsoft References
Intents vs Entities in Language Understanding
Prebuilt entity: GeographyV2
LUIS domains overview


NEW QUESTION # 331
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:


NEW QUESTION # 332
Match the types of workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may he used once, more than once, or not at all.
NOTE: Each correct match is worth one point.

Answer:

Explanation:


NEW QUESTION # 333
......

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