Multimatics

Academy | Syllabus

Microsoft Certified: Azure AI Fundamentals

The Microsoft Azure AI Fundamentals (AI-900) exam validates foundational knowledge of AI concepts and Azure services, focusing on artificial intelligence workloads, machine learning principles, computer vision, natural language processing (NLP), and generative AI. It is designed for beginners wanting to demonstrate AI literacy.

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Trusted by OrganizationsProven by Professionals

+21

Years of Experiences

+6.000

Delivered Training Programs

+50.000

Professionals

90%

Exam Pass Rate

Program Details

Durations

 The program is a 5-day intensive training class. 

Method of Delivery

The program provided by Multimatics will be delivered through interactive presentation by professional instructor(s), group debriefs, individual and team exercises, behavior modelling and roleplays, one-to-one and group discussion, case studies, and projects.  

Who Should Attend?

Beginners, technical professionals, students, and business leaders.

Program Objectives

By the end of the program, participants will be able to:

  • Identify key AI principles (fairness, reliability, safety, privacy, security, inclusiveness, transparency) and common AI scenarios (e.g., knowledge mining, computer vision, natural language processing).
  • Understand regression, classification, clustering, and reinforcement learning. Learn to use automated machine learning (AutoML) and Azure Machine Learning studio.
  • Identify tasks like image classification, object detection, semantic segmentation, optical character recognition (OCR), and facial recognition using Azure Cognitive Services.
  • Understand language modeling, sentiment analysis, key phrase extraction, text translation, and speech recognition.
  • Describe large language models (LLMs), prompt engineering, and the capabilities of Azure OpenAI Service.
  • Build and deploy chatbots using tools like Azure Bot Service.

Examination Details

Duration

45 Minutes

Format

    Open BookClose Book

Level

-

Passing Grade

65%

Program Modules

Describe Artificial Intelligence Workloads and Considerations

Topic Covered

  • Identify features of common AI workloads
  • Identify computer vision workloads
  • Identify natural language processing workloads
  • Identify document processing workloads
  • Identify features of generative AI workloads
  • Identify guiding principles for responsible AI
  • Describe considerations for fairness in an AI solution
  • Describe considerations for reliability and safety in an AI solution
  • Describe considerations for privacy and security in an AI solution
  • Describe considerations for inclusiveness in an AI solution
  • Describe considerations for transparency in an AI solution
  • Describe considerations for accountability in an AI solution