AI-900 - Azure AI Fundamentals and Two Practice Tests from Coursera

A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course.

In this course, you will gain a strong understanding of Azure AI fundamentals, preparing you for the Microsoft AI-900 exam. From grasping the core concepts of Artificial Intelligence (AI) to understanding how machine learning, computer vision, and natural language processing work on Azure, you’ll learn how AI is applied in real-world scenarios. By the end of this course, you will be able to describe Azure AI services, workloads, and principles in depth, providing you with the skills to develop AI solutions using Azure's advanced tools.

Throughout the course, you’ll explore fundamental AI concepts and tools such as Azure Cognitive Services, Azure Machine Learning, and Azure Cognitive Search. You'll dive into machine learning workflows, covering regression, classification, and clustering techniques, and understand how Azure facilitates these processes. The course also offers insights into the practical application of AI through demonstrations and hands-on sessions with Azure tools.

Whether you're new to Azure or aiming to solidify your knowledge, this course will guide you step-by-step through the fundamentals of Azure AI. The curriculum also prepares you for the AI-900 exam with real-world example questions, helping you hone your critical thinking and exam techniques.

This course is ideal for individuals seeking to break into AI with Microsoft Azure, those preparing for the AI-900 certification exam, or anyone interested in understanding AI workloads on the Azure platform. No prior AI or Azure knowledge is required, making it suitable for beginners in the field.

What's inside

Syllabus

Introduction to Azure AI-900

In this module, we will provide an overview of the AI-900 exam, walking through its contents and key topics. We’ll also discuss strategies for effective exam preparation, ensuring you’re ready for success on test day.

Career center

Learners who complete AI-900 - Azure AI Fundamentals and Two Practice Tests will develop knowledge and skills that may be useful to these careers:

Computer Vision Engineer

A Computer Vision Engineer develops algorithms and systems that allow computers to 'see' and interpret images and videos, crucial for applications like object detection, facial recognition, and image analysis. For an aspiring Computer Vision Engineer, this course provides a strong foundation by exploring how Azure’s computer vision services can be applied to solve real-world challenges. From analyzing images and videos to understanding how to train custom models, the curriculum offers insights into diverse applications of computer vision in Azure. This direct exposure to Azure Cognitive Services for vision helps establish the necessary initial understanding of tools and techniques for building and deploying vision-based AI solutions.

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Natural Language Processing Developer

A Natural Language Processing Developer builds systems that enable computers to understand, interpret, and generate human language, creating solutions for tasks such as text analysis, speech recognition, and language translation. For those pursuing a career as a Natural Language Processing Developer, this course offers direct and in-depth exposure to NLP workloads on Azure. It guides learners through text and speech analytics, sentiment analysis, translation, and language understanding tools, providing practical insights into building intelligent systems that process human language. The specific focus on Azure's NLP services, including Language Understanding, helps establish a solid foundation for developing and deploying robust NLP applications within the Azure ecosystem.

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Azure Cloud Engineer AI Specialist

An Azure Cloud Engineer AI Specialist focuses on building, maintaining, and optimizing the cloud infrastructure that supports artificial intelligence workloads on Microsoft Azure. This role ensures the underlying cloud environment is robust, scalable, and secure for AI deployments. For an Azure Cloud Engineer AI Specialist, this course provides an essential introduction to Azure AI fundamentals. Understanding Azure AI services, workloads, and how machine learning, computer vision, natural language processing, and conversational AI operate within the Azure ecosystem is crucial. This fundamental knowledge helps in configuring and managing the necessary Azure resources and services that empower AI solutions, ensuring the infrastructure optimally supports the development and deployment of AI applications.

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AI Engineer

An AI Engineer designs, develops, and deploys artificial intelligence solutions, translating business requirements into technical specifications and building AI models leveraging cloud platforms. For individuals aspiring to become an AI Engineer, this course provides an essential understanding of Azure AI fundamentals, including machine learning, computer vision, natural language processing, and conversational AI services. Learning about Azure Cognitive Services and Azure Machine Learning directly supports the practical skills needed to implement and manage AI workloads on the Azure platform. This foundational knowledge helps in understanding how to apply responsible AI principles and utilize Azure's vast toolkit for real-world AI applications.

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Conversational AI Designer

A Conversational AI Designer creates and optimizes interactive dialogue systems, such as chatbots and virtual assistants, to provide engaging and effective user experiences. This involves designing conversation flows and integrating AI services to understand user intent. For those interested in becoming a Conversational AI Designer, this course focuses on building conversational AI solutions using Azure services like QnA Maker and Language Understanding. Learners are guided through creating intelligent bots, enhancing them with active learning, and understanding their deployment in real-world scenarios. This direct practical exposure to Azure's conversational AI tools is invaluable for designing intuitive and functional AI-driven communication systems, laying a strong groundwork for this specialized career path.

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Azure AI Technical Trainer

An Azure AI Technical Trainer educates individuals and teams on Azure Artificial Intelligence services and concepts, designing and delivering workshops, courses, and presentations to help learners grasp complex AI topics. For an aspiring Azure AI Technical Trainer, this course provides comprehensive preparation, covering core AI concepts, machine learning principles, computer vision, natural language processing, and conversational AI on Azure. The structure, designed to prepare for the AI-900 exam, ensures a thorough understanding of Azure AI workloads, services, and responsible AI principles. This curriculum is an excellent resource for building the foundational expertise necessary to effectively explain and demonstrate Azure AI technologies to others.

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AI Solutions Consultant

An AI Solutions Consultant advises clients on the best strategies for integrating artificial intelligence into their operations, often involving the design and implementation of bespoke AI systems. This professional requires both technical knowledge and client-facing skills. For an AI Solutions Consultant, this course provides an excellent foundational understanding of Azure AI services, workloads, and principles. The curriculum's exploration of machine learning, computer vision, natural language processing, and conversational AI on Azure equips one with the knowledge to discuss various AI capabilities and their real-world applications. This comprehension of Azure's advanced tools helps in crafting effective, responsible, and practical AI solutions tailored to client needs.

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Cloud Solutions Architect AI

A Cloud Solutions Architect AI designs and oversees the implementation of scalable, reliable, and secure AI solutions within a cloud environment, creating the blueprint for how AI technologies integrate with existing systems. For those aiming to be a Cloud Solutions Architect AI, this course offers a foundational comprehension of Azure AI services and workloads. Understanding machine learning principles, computer vision, natural language processing, and conversational AI as implemented on Azure allows one to conceptualize robust AI architectures. The curriculum's focus on Azure Cognitive Services and Azure Machine Learning is particularly relevant for designing efficient and effective cloud-based AI solutions, ensuring the architect can make informed decisions about technology choices.

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Machine Learning Operations Specialist

A Machine Learning Operations Specialist focuses on the deployment, monitoring, and maintenance of machine learning models in production environments, ensuring that AI solutions are robust, scalable, and perform optimally over time. For individuals targeting a Machine Learning Operations Specialist role, this course provides a crucial understanding of fundamental machine learning principles and how they are implemented on Azure Machine Learning. Familiarity with regression, classification, and clustering techniques, coupled with knowledge of Azure's tools, forms a strong basis for understanding the lifecycle of ML models. The course also helps in comprehending how Azure AI services integrate into operational workflows, allowing for more effective management of AI workloads in real-world scenarios.

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Data Scientist AI Focus

A Data Scientist AI Focus extracts insights from complex datasets and develops predictive models, often leveraging artificial intelligence techniques, to solve business problems and drive strategic decisions. For an aspiring Data Scientist AI Focus, this course offers valuable foundational knowledge of AI concepts and their application on Azure. Understanding machine learning principles like regression, classification, and clustering, along with exposure to Azure Machine Learning, provides a strong starting point for analytical model development. Furthermore, an awareness of Azure's computer vision, natural language processing, and conversational AI services can inform advanced analytical approaches and enhance the ability to work with diverse data types. An advanced degree is often expected for this role.

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AI Business Analyst

An AI Business Analyst bridges the gap between business needs and AI solutions, identifying opportunities for AI adoption and defining requirements for AI projects. This professional translates strategic goals into tangible AI use cases. For an AI Business Analyst, this course is highly relevant as it provides a robust understanding of Azure AI fundamentals, including machine learning, computer vision, natural language processing, and conversational AI workloads. Comprehending how AI is applied in real-world scenarios and describing Azure AI services in depth allows one to effectively assess AI capabilities and communicate with technical teams. This foundational knowledge helps in identifying viable AI initiatives and articulating their potential impact.

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Technical Project Manager AI Focus

A Technical Project Manager AI Focus oversees the planning, execution, and delivery of artificial intelligence projects, ensuring they meet objectives, timelines, and budgets. This role requires a blend of management skills and technical acumen. For a Technical Project Manager AI Focus, this course helps build a foundational understanding of Azure AI fundamentals, including machine learning, computer vision, natural language processing, and conversational AI solutions. Comprehending Azure AI services and workloads allows for better communication with technical teams, more accurate estimation of project scope, and effective management of risks associated with AI development. This knowledge facilitates informed decision-making throughout the project lifecycle, supporting successful AI solution deployment.

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Product Manager AI Products

A Product Manager AI Products defines the strategy, roadmap, and features for AI-powered products, guiding their development from conception to launch. This role involves understanding market needs, technology capabilities, and user experience. For a Product Manager AI Products, this course provides a foundational understanding of Azure AI services, workloads, and core principles. Familiarity with machine learning, computer vision, natural language processing, and conversational AI on Azure helps in evaluating technical feasibility, understanding development cycles, and making informed product decisions. Knowing the capabilities and limitations of Azure's AI tools is crucial for defining features and communicating effectively with engineering teams, even if not directly building solutions.

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AI Ethics and Governance Specialist

An AI Ethics and Governance Specialist focuses on ensuring that artificial intelligence systems are developed and used responsibly, ethically, and in compliance with relevant regulations. This role involves establishing guidelines and assessing potential biases or societal impacts. For an AI Ethics and Governance Specialist, this course is particularly relevant due to its explicit coverage of responsible AI principles. Understanding the fundamental concepts of AI workloads on Azure, coupled with an awareness of ethical considerations discussed in the curriculum, provides a solid foundation for assessing AI systems. This knowledge helps in evaluating how Azure AI services are applied and identifying potential ethical challenges in machine learning, computer vision, natural language processing, and conversational AI deployments. An advanced degree is often beneficial or expected for this role.

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Robotics Process Automation Developer with AI

A Robotic Process Automation Developer with AI creates software robots to automate repetitive tasks, often enhancing these automations with artificial intelligence capabilities for intelligent processing and decision-making. This role combines process optimization with AI integration. For a Robotic Process Automation Developer with AI, this course may be useful by providing foundational knowledge of Azure AI services, particularly natural language processing and computer vision. Understanding how these AI tools work to process unstructured data or recognize patterns in images can significantly enhance the capabilities of RPA bots. Familiarity with fundamental AI concepts on Azure helps in identifying opportunities to embed intelligent components into automation workflows, creating more sophisticated and adaptive solutions.

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