Certainly! Here are the minimum required prerequisites for students intending to undertake the AI-900T00: Microsoft Azure AI Fundamentals course:

• Basic understanding of computing concepts: Familiarity with the core computing principles, including what a computer program is and what a network is.
• Fundamental knowledge of data concepts: An understanding of how data is stored and processed, including knowledge of databases and basic data types.
• Introductory level of mathematics: A grasp of basic mathematical concepts, including algebra and statistics, which are foundational to understanding machine learning algorithms.
• General understanding of cloud computing: Awareness of cloud services and cloud models (IaaS, PaaS, SaaS) is helpful, as Azure is a cloud platform.
• No prior experience with Azure is required: While experience with Azure can be beneficial, it is not a prerequisite for this course. The fundamentals will be covered during the training.
• Interest and willingness to learn about AI and machine learning: A curiosity about artificial intelligence, machine learning, and their applications in real-world scenarios.
• Proficiency in English: Since the course material and instructions are in English, proficiency in reading and understanding technical English is important.

Please note that while these are the minimum prerequisites, individuals with additional experience in programming, data science, or working with Microsoft Azure may find it easier to grasp the more technical aspects of the course. However, the course is designed to be accessible even for those with just the foundational knowledge listed above.

Target Audience for AI-900T00: Microsoft Azure AI Fundamentals

1. The AI-900T00: Microsoft Azure AI Fundamentals course provides foundational knowledge in AI and Azure services for beginners in tech and AI enthusiasts.

   
   

2. Target Audience and Job Roles:

   
   

• IT professionals interested in AI technologies
• Data Analysts seeking to understand AI applications
• Software Developers looking to integrate AI into their solutions
• Cloud Solution Architects exploring Azure AI capabilities
• Data Scientists beginning with Azure AI tools and services
• AI hobbyists and enthusiasts aiming to formalize their knowledge
• Technical Managers overseeing AI-driven projects
• Students studying computer science or related fields
• Non-technical roles seeking to comprehend the impact of AI in their industry (e.g., Business Analysts, Project Managers)
• Professionals working in industries where AI is increasingly relevant, such as healthcare, finance, and retail
• Educators and trainers preparing to teach AI fundamentals
• Career changers entering the AI and tech field

Learning Objectives - What you will Learn in this AI-900T00: Microsoft Azure AI Fundamentals?

Introduction to the AI-900T00: Microsoft Azure AI Fundamentals Course Learning Outcomes and Concepts:

This course provides foundational knowledge of AI concepts, machine learning, vision, natural language processing, and conversational AI using Azure services.

Learning Objectives and Outcomes:

• Understand the core principles and applications of AI, including an overview of Azure's AI capabilities and the importance of Responsible AI.
• Gain knowledge of fundamental machine learning concepts and how to apply automated machine learning with Azure Machine Learning.
• Explore the essentials of computer vision, facial recognition, and optical character recognition, including hands-on experience with Vision Studio.
• Learn about the introduction to machine learning and its implementation through Azure Machine Learning services.
• Comprehend key computer vision concepts and how to implement them using Azure's computer vision services.
• Acquire skills in analyzing text, question answering, conversational language understanding, and speech services with Azure's Language and Speech Studios.
• Understand the basics of document intelligence, knowledge mining, and how to utilize Azure AI Search to extract insights from documents.
• Familiarize with Natural Language Processing (NLP) features and workloads on Azure for analyzing and processing language data.
• Explore conversational AI concepts and how to build solutions with Azure's conversational AI services.
• Learn about generative AI, responsible use cases, and how to leverage Azure OpenAI Service for AI-powered applications.