Exam AI-900 Microsoft Azure AI Fundamentals
Exam AI-900 Microsoft Azure AI Fundamentals
Exam AI-900 Microsoft Azure AI Fundamentals
Instructor: Tim Warner


Prepare to become an AI professional and ace the Microsoft Exam AI-900 with our comprehensive video course from Microsoft Press, covering everything from the fundamentals of AI to practical applications using Azure AI services.

In healthcare, AI is used for medical image analysis, drug discovery, and predicting patient outcomes. In finance, AI is used for fraud detection, credit scoring, and algorithmic trading. In retail, AI is used for recommendation systems, supply chain optimization, and inventory management. In manufacturing, AI is used for predictive maintenance, quality control, and autonomous robotics. In customer service, AI is used for chatbots, sentiment analysis, and personalized marketing.

These are just a few examples of how AI technologies are being used in the real world, and the demand for professionals with the skills to develop and implement these technologies is rapidly .

Skill Level:

Beginner
Intermediate

What You Will Learn:

After completing this video, you will be able to:

  • Understand fundamental principles of machine learning on Azure
  • Work with all features of computer vision workloads on Azure
  • Experiment with features of Natural Language Processing (NLP) workloads on Azure

Who Should Take This Course:

  • Data analysts or scientists who want to expand their skills to include AI and machine learning.
  • Software developers or engineers who want to incorporate AI capabilities into their software applications.
  • IT professionals who want to learn how to leverage AI technologies in their organization.
  • Project managers or team leaders who want to understand the potential impact of AI on their organization.
  • Students or recent graduates who want to gain a basic understanding of AI concepts and how they can be applied in different industries.

Prerequisite:

This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, awareness of cloud basics and client-server applications would be beneficial.

More Info

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