Learning Tree USA - SCHEV - Introduction to AI in Azure (AI-900)

Learning Tree's Azure AI Introduction training provides fundamental concepts related to artificial intelligence in Microsoft Azure to create AI solutions. This SCHEV-approved Microsoft Azure AI Indroduction Training introduces AI and the Microsoft services students can use to create AI solutions.

*Terms and Conditions: This course is offered by Learning Tree USA, a school certified by the State Council of Higher Education for Virginia (SCHEV) to operate in Virginia. Offer Valid for Virginia residents only. The promotion is only valid for the September 23, 2025 AI-900 course. All attendees must fill-out and sign an attendee enrollment agreement prior to course attendance.

Learning Tree USA - SCHEV - Introduction to AI in Azure (AI-900) Benefits

• In this course, you will:

  • Gain a solid foundation in AI concepts including machine learning, NLP, computer vision, and generative AI.
  • Learn hands-on with Azure AI Foundry to build and test intelligent applications.
  • Understand real-world applications of AI such as text analysis, speech recognition, image analysis, and information extraction.
  • Explore responsible AI practices to design solutions that are ethical and trustworthy.
  • Prepare for more advanced AI projects by establishing a strong base in both theory and Azure tools.

• Prerequisites:

  Prerequisite certification is not required before taking this course. However, successful Azure AI Fundamental students start with essential knowledge of computing and internet concepts and an interest in using Azure AI services.

  Before taking this course, students should have:

  • Experience using computers and the internet.
  • Interest in use cases for AI applications and machine learning models.
  • A willingness to learn through hands-on exploration.

• Exam Information:

  This course can help you prepare for the following Microsoft role-based certification exam — Exam AI-900: Microsoft Certified: Azure AI Fundamentals.

Introduction to AI in Azure Training Outline

Learning Objectives

Chapter 1: Introduction to AI Concepts

• Explore core AI topics including generative AI, computer vision, speech, natural language processing, and responsible AI.

Chapter 2: Introduction to Machine Learning Concepts

• Understand machine learning types, regression, classification, clustering, deep learning, and transformers.

Chapter 3: Get Started with Machine Learning in Azure

• Learn to define problems, prepare data, train models, and use Azure Machine Learning Studio.

Chapter 4: Introduction to Generative AI Concepts

• Discover how language models and transformers generate original content and apply responsible practices.

Chapter 5: Get Started with Generative AI in Azure

• Use Azure AI Foundry’s tools, model catalog, and playgrounds to build generative AI apps.

Chapter 6: Introduction to Natural Language Processing Concepts

• Learn the fundamentals of NLP, from statistical techniques to semantic models.

Chapter 7: Get Started with Natural Language Processing in Azure

• Apply Azure AI Language services for sentiment analysis, conversational AI, and translation.

Chapter 8: Get Started with Speech in Azure

• Recognize and synthesize speech with Azure AI Speech services.

Chapter 9: Introduction to Computer Vision Concepts

• Explore image processing, modern vision models, and machine learning for vision.

Chapter 10: Get Started with Computer Vision in Azure

• Use Azure AI Vision services to analyze images and detect faces.

Chapter 11: Introduction to AI-Powered Information Extraction Concepts

• Understand how to extract data from images, forms, and multimodal sources.

Chapter 12: Get Started with AI-Powered Information Extraction in Azure

• Use Azure AI services to extract insights, build knowledge mining solutions, and analyze documents.