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One of the key objectives of the Microsoft AI-102 exam is to test candidates' ability to design and implement machine learning models using Azure Machine Learning. This includes understanding how to select appropriate algorithms, prepare data for training, and fine-tune models to achieve the best possible performance. Candidates will also be tested on their ability to deploy machine learning models as web services using Azure Kubernetes Service (AKS).
The AI-102 Certification Exam is an advanced-level certification that requires a deep understanding of Microsoft Azure and AI technologies. Candidates who pass AI-102 exam will be able to demonstrate their expertise in designing and implementing AI solutions using Microsoft Azure. They will also be able to use their knowledge to help organizations leverage AI technologies to improve their business processes and gain a competitive edge in the market.
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Microsoft AI-102 exam is aimed at professionals who have experience in AI solution development and deployment. The candidates should have a good understanding of machine learning algorithms and should be able to apply them in real-world scenarios. AI-102 Exam also tests the candidate's ability to design and integrate AI solutions with other Azure services.
NEW QUESTION # 419
You have an Azure subscription. The subscription contains an Azure OpenAI resource that hosts a GPT-3.5 Turbo model named Model1.
You configure Model1 to use the following system message: "You are an Al assistant that helps people solve mathematical puzzles. Explain your answers as if the request is by a 4-year-old." Which type of prompt engineering technique is this an example of?
Answer: B
NEW QUESTION # 420
Match the Azure services to the appropriate locations in the architecture.
To answer, drag the appropriate service from the column on the left to its location on the right. Each service may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
NEW QUESTION # 421
You build a chatbot by using Azure OpenAI Studio.
You need to ensure that the responses are more deterministic and less creative.
Which two parameters should you configure? To answer, select the appropriate parameters in the answer area.
NOTE: Each correct answer is worth one point.
Answer:
Explanation:
NEW QUESTION # 422
You plan to build a chatbot to support task tracking.
You create a Language Understanding service named lu1.
You need to build a Language Understanding model to integrate into the chatbot. The solution must minimize development time to build the model.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. (Choose four.)
Answer:
Explanation:
Explanation:
1. Add a new application
2. Add a prebuilt domain intent ToDo (it has already utterances so we can skip this step)
3. Train
4. Publish
NEW QUESTION # 423
You have an Azure subscription that contains an Azure OpenAl resource. Multiple different models are deployed to the resource.
You are building a chatbot by using Chat playground in Azure Al Studio.
You need to ensure that the chatbot generates text in concise formal business language. The solution must meet the following requirements:
* Reduce the cost of running the language model.
* Maintain the size of the chatbot history window.
Which two settings should you configure? To answer, select the appropriate settings in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Scenario Recap:
* You have an Azure OpenAI resource with multiple deployed models.
* You are using the Chat playground to build a chatbot.
* Requirements:
* Generate text in concise, formal business language.
* Reduce cost of running the model.
* Maintain the size of the chatbot history window (i.e., context length).
Step 1: Ensuring concise, formal business language In the Chat playground setup panel, you can configure System message instructions.
Example:
You are an AI assistant that responds in concise formal business language.
This controls tone, style, and response behavior.
So one setting is: System message / Instructions.
Step 2: Reducing cost while maintaining chat history window Costs in Azure OpenAI are tied to:
* The model used (larger models = more expensive).
* The context window size (token usage).
Since we must maintain the size of the chat history window, we cannot shrink context length.
Therefore, to reduce cost: select a smaller/cheaper deployed model (e.g., GPT-3.5 instead of GPT-4).
So the second setting is: Deployment (model selection).
* Configure Deployment # choose a smaller/cheaper model.
* Configure System message instructions # specify "concise formal business language."
# Final Answer:
Microsoft References:
* Azure OpenAI Chat playground
* Best practices for reducing token cost
NEW QUESTION # 424
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