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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Language - Describe capabilities of Azure Translator - Describe capabilities of Azure Speech - Identify types of NLP solutions |
| Topic 2: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision - Identify types of computer vision solutions |
| Topic 3: Features of generative AI workloads on Azure | 20–25% | - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI - Describe generative AI concepts - Describe use cases for generative AI |
| Topic 4: Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe capabilities of Azure Machine Learning - Describe machine learning pipelines - Describe core concepts of machine learning |
| Topic 5: Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe responsible AI principles - Describe considerations for developing AI solutions |
CertkingdomPDF Microsoft AI-900 Practice Test give you the opportunity to practice for the Microsoft AI-900 new exam questions. By using Microsoft Practice Test, you can get the ideal possibility to know the actual Microsoft Azure AI Fundamentals exam, as they follow the same interface as the real exam. This way, you can become more confident and comfortable while taking the actual exam.
NEW QUESTION # 290
You have the following dataset.
You plan to use the dataset to train a model that will predict the house price categories of houses.
What are Household Income and House Price Category? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/interpret-model-results
NEW QUESTION # 291
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 292
Match the Azure OpenAI large language model (LLM) process to the appropriate task.
To answer, drag the appropriate process from the column on the left to its task on the right. Each process may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) study material and Azure OpenAI Service documentation, large language models (LLMs) such as GPT are capable of performing multiple natural language processing (NLP) tasks depending on the intent of the prompt. These tasks generally fall into categories like classification, generation, summarization, and translation, each with a distinct purpose and output type.
* Classifying - This process involves analyzing text and assigning it to a predefined category or label based on its content. The scenario "Detect the genre of a work of fiction" clearly fits this category. The model must evaluate the text and determine whether it belongs to genres like mystery, romance, or science fiction. This is a classic text classification problem, as the output is a discrete category derived from textual features.
* Summarizing - This process means condensing lengthy text into a shorter version that preserves the key information. In the scenario "Create a list of bullet points based on text input," the model extracts essential information and reformats it as concise bullet points, which is an abstraction form of summarization. Summarization models help users quickly understand the main ideas from long documents, meeting efficiency and readability goals.
* Generating - This refers to the LLM's ability to produce new, creative content based on input instructions. The task "Create advertising slogans from a product description" represents generation because it requires the model to construct original text that didn't previously exist. Generation tasks showcase the creativity and contextual fluency of models like GPT in marketing and content creation.
Thus, these mappings align directly with the Azure OpenAI LLM capabilities taught in AI-900, linking each NLP process with its most suitable real-world task.
NEW QUESTION # 293
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:
NEW QUESTION # 294
Match the services to the appropriate descriptions.
To answer, drag the appropriate service from the column on the left to its description 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:
Explanation:
NEW QUESTION # 295
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