Microsoft Azure AI Fundamentals Certification

Microsoft Azure AI Fundamentals Certification - Certification & Exam

This exam is intended for candidates with varying backgrounds, including those without data science or software engineering experience. However, having a basic understanding of cloud concepts and client-server applications can be beneficial. The Azure AI Fundamentals certification is valuable for preparing for other Azure role-based certifications, such as Azure Data Scientist Associate or Azure AI Engineer Associate, though it is not a prerequisite for any of them.

The AI-900 exam measures your ability to understand and describe:

Describe Artificial Intelligence Workloads and Considerations 

• Identify Features of Common AI Workloads:

  • Anomaly detection workloads
  • Computer vision workloads
  • Natural language processing workloads
  • Knowledge mining workloads

• Identify Guiding Principles for Responsible AI:

  • Fairness in AI solutions
  • Reliability and safety in AI solutions
  • Privacy and security in AI solutions
  • Inclusiveness in AI solutions
  • Transparency in AI solutions
  • Accountability in AI solutions

Describe Fundamental Principles of Machine Learning on Azure 

• Identify Common Machine Learning Types:

  • Regression machine learning scenarios
  • Classification machine learning scenarios
  • Clustering machine learning scenarios

• Describe Core Machine Learning Concepts:

  • Features and labels in a dataset for machine learning
  • Training and validation datasets usage in machine learning

• Describe Capabilities of Visual Tools in Azure Machine Learning Studio:

  • Automated machine learning
  • Azure Machine Learning designer

Describe Features of Computer Vision Workloads on Azure 

• Identify Common Types of Computer Vision Solutions:

  • Image classification solutions
  • Object detection solutions
  • Optical character recognition solutions
  • Facial detection, recognition, and analysis solutions

• Identify Azure Tools and Services for Computer Vision Tasks:

  • Computer Vision service
  • Custom Vision service
  • Face service
  • Form Recognizer service

Describe Features of Natural Language Processing (NLP) Workloads on Azure 

• Identify Features of Common NLP Workload Scenarios:

  • Key phrase extraction
  • Entity recognition
  • Sentiment analysis
  • Language modeling
  • Speech recognition and synthesis
  • Translation

• Identify Azure Tools and Services for NLP Workloads:

  • Language service
  • Speech service
  • Translator service

• Identify Considerations for Conversational AI Solutions on Azure:

  • Features and uses for bots
  • Capabilities of the Azure Bot service

Benefits of the certification 

• Earning the Microsoft Azure AI Fundamentals certification demonstrates your commitment and foundational understanding of AI and cloud services.
•  Enhance your resume and improve your job prospects in the growing field of AI.
• Gain a comprehensive understanding of AI concepts and Azure services, enabling you to apply these skills in real-world scenarios.
•  This certification serves as a stepping stone for more advanced Azure certifications, such as the Azure AI Engineer Associate and Azure Data Scientist Associate.