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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: 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 |
| Topic 2: Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Ingest and process structured/unstructured data - Implement intelligent search and retrieval |
| Topic 3: Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources |
| Topic 4: Implement computer vision solutions | 10-15% | - Process and index video content - Extract text and handwriting from images - Integrate vision capabilities into applications - Analyze images and detect objects/features - Build and deploy custom vision models |
| Topic 5: Implement generative AI solutions | 15-20% | - Deploy and manage generative models - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback |
| Topic 6: Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection - Customize and deploy NLP models |
>> Microsoft AI-102 Latest Test Answers <<
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NEW QUESTION # 198
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Data Analyst.
When dealing with data roles in an organization, responsibilities are divided among data analysts, data engineers, and data scientists. Let's review them:
* Data Analyst
* Focuses on understanding business requirements and ensuring that the right rules and logic are applied to data so it becomes meaningful for decision-making.
* They work closely with stakeholders to define business rules such as data validation rules, aggregation logic, and reporting metrics.
* This makes them responsible for identifying which business rules must be applied to data.
* Data Engineer
* Responsible for designing, building, and maintaining the infrastructure and pipelines that move and process data.
* They ensure data availability, reliability, and scalability, but do not usually define business rules.
* Data Scientist
* Focuses on advanced analytics, predictive modeling, and machine learning.
* They use data prepared by engineers and analysts but are not typically the ones who define the business rules that govern how raw data should be interpreted.
Therefore, the correct answer is Data Analyst.
A data analyst
* Data roles and responsibilities in Azure
* What is a Data Analyst?
* Responsibilities of Data Engineers vs Data Scientists vs Data Analysts Microsoft References
NEW QUESTION # 199
You are developing a text processing solution.
You develop the following method.
You call the method by using the following code.
GetKeyPhrases(textAnalyticsClient, "the cat sat on the mat");
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-keyword-extraction
NEW QUESTION # 200
You are developing a text processing solution.
You develop the following method.
You call the method by using the following code.
GetKeyPhrases(textAnalyticsClient, "the cat sat on the mat");
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Yes
The Key Phrase Extraction API evaluates unstructured text, and for each JSON document, returns a list of key phrases.
Box 2: No
'the' is not a key phrase.
This capability is useful if you need to quickly identify the main points in a collection of documents. For example, given input text "The food was delicious and there were wonderful staff", the service returns the main talking points: "food" and "wonderful staff".
Box 3: No
Key phrase extraction does not have confidence levels.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-keyword-
NEW QUESTION # 201
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Azure Synapse Analytics (formerly Azure SQL Data Warehouse) uses a massively parallel processing (MPP) architecture for big data and analytics workloads.
* Control Node:
* Acts as the brain of the system.
* Receives queries, optimizes them, and then coordinates execution.
* Does not perform large-scale data crunching itself.
* Compute Nodes:
* Perform the actual parallel execution of queries.
* Data is distributed across these nodes.
* The MPP engine breaks down queries into smaller tasks and distributes them to compute nodes for fast, parallel execution.
* Distributes processing across compute nodes # Correct. This is the essence of MPP.
* Distributes processing across control nodes # Incorrect. The control node does not process queries in parallel; it coordinates them.
* Redirects client connections across compute nodes # Incorrect. Client connections go to the control node, not directly to compute nodes.
* Redirects client connections across control nodes # Incorrect. There is typically one control node per Synapse instance.
Review of Answer Options:
The answer: Distributes processing across compute nodes
* Azure Synapse Analytics architecture
* Distributed query processing in Azure Synapse
Microsoft References
NEW QUESTION # 202
You need to develop code to upload images for the product creation project. The solution must meet the accessibility requirements.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://github.com/Azure-Samples/cognitive-services-dotnet-sdk-samples/blob/master/documentation-samples/quickstarts/ComputerVision/Program.cs
NEW QUESTION # 203
......
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