AI-901 Online Praxisprüfung, AI-901 Pruefungssimulationen

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Microsoft AI-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Describe features of computer vision workloads on Azure	15-20%	- Azure AI Vision services 1. Azure AI Vision 2. Face detection and analysis (limited use cases) - Image analysis 1. Object detection 2. Image classification 3. Optical character recognition (OCR)
Topic 2: Describe features of generative AI workloads on Azure	10-15%	- Azure OpenAI and generative services 1. Use cases: chatbots, content generation, summarization 2. Azure OpenAI Service capabilities - Generative AI concepts 1. Large language models (LLMs) 2. Responsible use of generative AI 3. Prompt engineering basics
Topic 3: Describe Artificial Intelligence workloads and considerations	20-25%	- Identify features of common AI workloads 1. Conversational AI and chatbots 2. Natural language processing use cases 3. Computer vision use cases 4. Document processing and extraction - Responsible AI principles 1. Transparency and accountability 2. Reliability and safety 3. Privacy and security 4. Fairness 5. Inclusiveness
Topic 4: Describe features of natural language processing (NLP) workloads on Azure	15-20%	- Azure NLP services 1. Speech services (speech-to-text, text-to-speech) 2. Azure AI Language - Text analysis 1. Language detection 2. Key phrase extraction 3. Sentiment analysis
Topic 5: Describe fundamental principles of machine learning on Azure	25-30%	- Machine learning concepts 1. Training and evaluation concepts 2. Regression and classification 3. Supervised vs unsupervised learning - Azure Machine Learning basics 1. AutoML concepts 2. Azure ML workspace components

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AI-901 Pruefungssimulationen, AI-901 Online Prüfungen

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Microsoft Azure AI Fundamentals AI-901 Prüfungsfragen mit Lösungen (Q29-Q34):

29. Frage
You have a dataset that contains experimental data for fuel samples.
You need to predict the amount of energy in kilojoules that can be obtained from a sample based on its measured density.
Which type of AI workload should you use?

A. Classification
B. Clustering
C. Regression
D. Knowledge mining

Antwort: C

Begründung:
Regression is a supervised machine learning technique which is used to predict continuous values. The ultimate goal of the regression algorithm is to plot a best-fit line or a curve between the data. The three main metrics that are used for evaluating the trained regression model are variance, bias and error.
Reference:
https://builtin.com/data-science/regression-machine-learning

30. Frage
Which action can be performed by using the Azure AI Vision service?

A. extracting key phrases from documents
B. extracting data from handwritten letters
C. creating thumbnails for training videos
D. identifying breeds of animals in live video streams

Antwort: B

Begründung:
Azure AI Vision is a service within Azure Cognitive Services that enables developers to analyze visual data from images and videos. It includes OCR (Optical Character Recognition) capabilities, allowing you to extract text (both printed and handwritten) from images, PDFs, and scanned documents.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/overview-ocr

31. Frage
Hotspot Question
Select the answer that correctly completes the sentence.

Antwort:

Begründung:

Explanation:
Box: Computer vision
Computer vision uses Optical Character Recognition (OCR) and deep learning models to detect, localize, and extract printed or handwritten text from images, turning visual pixels into editable digital data.
Reference:
https://docs.cloud.google.com/vision/docs/ocr

32. Frage
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Antwort:

Begründung:

Explanation:

Statement 1: Voice Live returns only transcribed text. = No
Voice Live is not limited to transcription. Microsoft documentation states that the Voice Live API supports real-time bidirectional voice applications, including speech recognition, text-to-speech synthesis, avatar streaming, animation data, and audio processing.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services.
= No
Voice Live provides a single real-time voice API experience rather than requiring separate STT and TTS implementations for the conversational loop. Microsoft describes live AI voice conversations as combining speech capabilities for real-time interaction, and the Voice Live API includes speech recognition and text-to- speech synthesis features.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This is correct. Microsoft's guidance explains that Azure OpenAI audio/realtime capabilities are for scenarios that combine audio with language understanding, reasoning, or generation in a single model call, and Voice Live supports real-time voice-enabled applications over WebSocket connections.

33. Frage
You deploy the Azure OpenAI service to generate images.
You need to ensure that the service provides the highest level of protection against harmful content.
What should you do?

A. Customize a large language model (LLM)
B. Configure the Content filters settings
C. Change the model used by the Azure OpenAI service
D. Configure the system prompt

Antwort: B

34. Frage
......

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