[74% Off] Microsoft Azure Ai Fundamentals Ai-900 Practice
Prepare for the AI-900 exam with practice tests covering Azure AI, ML, and cognitive services basics.
What you’ll learn
- Build technical skills to prepare for Microsoft Azure AI workloads.
- Interpret AI-900 exam-style questions with confidence.
- Apply machine learning fundamentals to Azure-based solutions.
- Understand AI workloads
- machine learning types
- and responsible AI principles.
- Understand AI workloads
- machine learning types
- and responsible AI principles.
Requirements
- No specific qualifications are needed to take this test.
Description
This course is designed to help you prepare effectively for the Microsoft Azure AI Fundamentals (AI-900) certification exam. By using carefully structured practice tests, you will strengthen your knowledge of artificial intelligence (AI), machine learning (ML), and Azure cognitive services while building the confidence needed to pass the AI-900 exam on your first attempt.The AI-900 certification validates foundational knowledge of AI concepts and how they are implemented in Microsoft Azure. It is ideal for students, beginners, and professionals who want to explore the field of artificial intelligence and understand how Azure provides solutions for AI workloads.
Exam Details
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Duration: 60 minutes
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Format: Multiple-choice and multiple-response questions
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Passing Score: 700 (out of 1000)
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Exam Languages: English (plus additional languages offered by Microsoft)
Through these practice tests, you will gain familiarity with the exam format, identify areas where you need improvement, and reinforce your knowledge of Azure AI services. Each question includes detailed explanations to help you understand the reasoning behind the correct answer.
Skills Measured by AI-900 Exam
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Describe AI workloads and considerations – understanding machine learning types, responsible AI principles, and data fundamentals.
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Describe fundamental principles of machine learning on Azure – supervised vs. unsupervised learning, features, labels, and model training.
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Describe features of computer vision workloads on Azure – image classification, object detection, and face recognition services.
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Describe features of Natural Language Processing (NLP) workloads on Azure – sentiment analysis, language understanding, and translation.
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Describe features of conversational AI workloads on Azure – chatbots, QnA Maker, and Azure Bot Service.
By practicing with real exam-style questions, you will be better prepared to handle the time pressure, question style, and concepts tested on the exam.
This course is not just about memorization — it focuses on helping you understand the core AI concepts that are critical to your success in both the exam and real-world applications.
