[100% Off] Ai-900: Microsoft Azure Ai Fundamentals – Full Practice Test
Azure AI Fundamentals: Master Responsible AI, Machine Learning, Computer Vision, and Generative AI with Azure.
What you’ll learn
- Define the principles of Responsible AI (Fairness
- Reliability
- Privacy
- Inclusiveness
- Transparency
- and Accountability).
- Identify common AI workloads including Machine Learning
- Computer Vision
- and Natural Language Processing (NLP).
- Describe fundamental Machine Learning concepts like regression
- classification
- clustering
- and the use of training/validation datasets.
- Identify Azure AI services for NLP and Generative AI (e.g.
- text analysis
- speech
- translation
- and Azure OpenAI Service).
Requirements
- No prior knowledge of data science or programming is required.
- A basic level of familiarity with computer technology and the Internet is assumed.
- Awareness of basic cloud concepts (like those covered in AZ-900) is beneficial but not mandatory.
Description
This comprehensive course is your essential, non-technical guide to mastering the AI-900: Microsoft Azure AI Fundamentals certification, offering a detailed exploration of core Artificial Intelligence (AI) concepts and the capabilities of Microsoft Azure’s AI services without requiring any prior programming or data science experience. We will systematically cover the official exam domains, starting with the critical principles of Responsible AI, ensuring you understand the ethical considerations of fairness, privacy, and transparency essential for modern solutions. The curriculum then delves into the fundamentals of Machine Learning (ML), where you will learn to distinguish between common techniques like regression, classification, and clustering, and discover how to leverage the power of Azure Machine Learning Studio’s visual and automated tools (AutoML). You will next gain expertise in recognizing the features of major AI workloads: Computer Vision, where we examine services for image classification, object detection, and OCR; and Natural Language Processing (NLP), covering text analytics, sentiment analysis, speech recognition, and translation using Azure AI Language and Speech services. Finally, the course provides a focused, up-to-date look at Generative AI and the cutting-edge Azure OpenAI Service, detailing its features for generating text and code, thereby equipping you with the foundational knowledge to confidently describe, implement, and govern various AI solutions within the Microsoft Azure ecosystem, successfully passing the AI-900 exam and solidifying your role as an informed professional in the cloud and AI space.
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