P.S. Free 2026 Microsoft AI-102 dumps are available on Google Drive shared by ExamTorrent: https://drive.google.com/open?id=1xRZTXh1necpL8J1IAeReXYLODnQO1D3p
It can be said that all the content of the AI-102 study materials are from the experts in the field of masterpieces, and these are understandable and easy to remember, so users do not have to spend a lot of time to remember and learn. It takes only a little practice on a daily basis to get the desired results. Especially in the face of some difficult problems, the user does not need to worry too much, just learn the AI-102 Study Materials provide questions and answers, you can simply pass the exam.
| Section | Weight | Objectives |
|---|---|---|
| Plan and manage an Azure AI solution | 20-25% | - Plan solutions aligned with responsible AI principles - Monitor, optimize, and secure AI solutions - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select suitable AI models - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources |
| Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Implement model monitoring and feedback - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Deploy and manage generative models |
| Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Develop multi-agent workflows and orchestration |
| Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Ingest and process structured/unstructured data |
| Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Implement translation and summarization - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection |
| Implement computer vision solutions | 10-15% | - Integrate vision capabilities into applications - Analyze images and detect objects/features - Build and deploy custom vision models - Process and index video content - Extract text and handwriting from images |
>> New AI-102 Test Objectives <<
The clients can try out and download our AI-102 study materials before their purchase. They can immediately use our AI-102 training guide after they pay successfully. And our expert team will update the AI-102 study materials periodically after their purchase and if the clients encounter the problems in the course of using our AI-102 Learning Engine our online customer service staff will enthusiastically solve their problems.
NEW QUESTION # 115
You are building a customer support chatbot.
You need to configure the bot to identify the following:
* Code names for internal product development
* Messages that include credit card numbers
The solution must minimize development effort.
Which Azure Cognitive Service for Language feature should you use for each requirement? To answer, drag the appropriate features to the correct requirements. Each feature may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The chatbot needs to recognize two different kinds of information:
Code names for internal product development
These are not standard entities like " locations " or " organizations " that prebuilt NER can detect.
You need to train a custom model to recognize internal terms or codenames (for example, " Project Falcon " ).
The correct Azure Cognitive Service for Language feature is Custom Named Entity Recognition (Custom NER), which allows defining and training entity categories specific to your business.
Messages that include credit card numbers
Credit card numbers are sensitive data falling under Personally Identifiable Information (PII).
Azure Cognitive Service for Language provides a PII detection feature that automatically identifies and masks sensitive information such as credit card numbers, SSNs, and phone numbers.
This minimizes development effort since it is prebuilt and ready to use.
Correct Answer Mapping:
Identify code names for internal product development # Custom named entity recognition (NER) Identify messages that include credit card numbers # Personally Identifiable Information (PII) detection Microsoft References Custom Named Entity Recognition in Azure AI Language PII detection in Azure AI Language
NEW QUESTION # 116
You have an Azure subscription that contain an Azure OpenAI resource named AI1.
You build a chatbot that uses AI1 to provide generation answers to specific questions.
You need to ensure that the chatbot checks all input output for objectionable content.
Which types of resource should you create first?
Answer: D
Explanation:
You have a chatbot built on Azure OpenAI (AI1). The requirement is that all input and output from the chatbot must be checked for objectionable content (such as hate speech, sexual, violent, or self-harm content).
To meet this requirement, Microsoft recommends integrating Azure AI Content Safety with Azure OpenAI.
* Azure AI Content Safety provides APIs to detect and filter harmful or objectionable text and images.
* For chatbot scenarios, you can configure Content Safety as a moderation layer on both user input (prompt) and model output (response).
* This ensures safe interactions before messages are returned to users.
Other options:
* A. Azure Machine Learning - used for building, training, and deploying custom ML models, not for content moderation.
* B. Log Analytics - used for monitoring and logging, not for filtering objectionable content.
* D. Microsoft Defender Threat Intelligence (Defender TI) - provides cybersecurity intelligence, not responsible for moderating chatbot content.
Therefore, the correct resource to create is Azure AI Content Safety.
C). Azure AI Content Safety
* Azure OpenAI and Azure AI Content Safety integration
* Azure AI Content Safety overview
* Moderate text with Azure AI Content Safety
Microsoft References
NEW QUESTION # 117
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Comprehensive Detailed ExplanationRelational databases (such as Azure SQL Database, SQL Server, or Azure Database for PostgreSQL) are designed for structured data and ACID-compliant transactions.
Let's analyze the options:
* Changes to relationships between entities
* While relational databases do handle relationships (via primary/foreign keys), this phrase alone does not describe the core usage scenario for "high volume."
* Geographically distributed writes
* This is better suited to NoSQL databases (e.g., Azure Cosmos DB) because they are optimized for global distribution and multi-region writes.
* Transactional writes
* Correct.
* Relational databases excel at handling large volumes of transactional operations (INSERT, UPDATE, DELETE) while ensuring consistency, integrity, and rollback capabilities.
* This is the primary workload for OLTP (Online Transaction Processing) systems.
* Writes that have varying data structures
* This is a use case for NoSQL/document databases like MongoDB or Azure Cosmos DB, not relational systems which require structured schema.
The answer: Transactional writes
* Azure SQL Database - transactional processing
* Data store considerations: relational vs non-relational
* OLTP vs OLAP
Microsoft References
NEW QUESTION # 118
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 have an Azure AI Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Azure AI Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You migrate to a Azure AI Search service that uses a higher tier.
Does this meet the goal?
Answer: A
Explanation:
A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing-based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
NEW QUESTION # 119
You develop an app in O named App1 that performs speech-to-speech translation.
You need to configure App1 to translate English to German.
How should you complete the speechTransiationConf ig object? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 120
......
The latest Designing and Implementing a Microsoft Azure AI Solution AI-102 exam and exam study guide is reliable, Designing and Implementing a Microsoft Azure AI Solution AI-102 with reasonable exam price and guaranteed questions answers. Microsoft offers actual Designing and Implementing a Microsoft Azure AI Solution to sure your success in AI-102 Exam. Don't worry, this Designing and Implementing a Microsoft Azure AI Solution AI-102 test price is benefit and content is 365 days updates!
AI-102 Valid Test Pdf: https://www.examtorrent.com/AI-102-valid-vce-dumps.html
BTW, DOWNLOAD part of ExamTorrent AI-102 dumps from Cloud Storage: https://drive.google.com/open?id=1xRZTXh1necpL8J1IAeReXYLODnQO1D3p