AI-900: Microsoft Azure AI Fundamentals Exam

About AI-900 exam

This exam is an opportunity to demonstrate knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services. Candidates for this exam should have familiarity with Exam AI-900's self-paced or instructor-led learning material.

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.

Exam Information

• In the main exam, you may get 35-50 questions
• Exam duration is 60 minutes
• Question types are single select, multiple select, Yes/No, Drag and Drop, Select from Drop-down and True/False
• You will require to score 700 points out from 1000 (My target for you to score 95% and more)
• The Good part is, there is no negative marking for wrong answers

Exam Topics

• Describe Artificial Intelligence workloads and considerations (15-20%)
• Describe fundamental principles of machine learning on Azure (20-25%)
• Describe features of computer vision workloads on Azure (15-20%)
• Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%)
• Describe features of generative AI workloads on Azure (15-20%)

How to Study the Topics

Describe Artificial Intelligence workloads and considerations

• Understand basic AI concepts and types of AI workloads
• Learn about responsible AI principles and practices
• Study common AI use cases and scenarios

Describe fundamental principles of machine learning on Azure

• Study core machine learning concepts
• Familiarize yourself with Azure Machine Learning workspace
• Learn about different types of machine learning (supervised, unsupervised, reinforcement)
• Understand the machine learning lifecycle and how it's implemented on Azure

Describe features of computer vision workloads on Azure

• Understand basics of computer vision
• Learn about Azure Cognitive Services for vision (e.g., Computer Vision API, Custom Vision)
• Study common computer vision tasks like image classification, object detection, and facial recognition

Describe features of Natural Language Processing (NLP) workloads on Azure

• Study fundamentals of NLP
• Learn about Azure services for NLP (e.g., Text Analytics, Translator Text)
• Understand common NLP tasks like sentiment analysis, language detection, and entity recognition

Describe features of generative AI workloads on Azure

• Understand the basics of generative AI
• Learn about Azure services that support generative AI tasks
• Study use cases and applications of generative AI in business scenarios

Additional Tips

• Use Microsoft Learn for free online training modules specifically designed for AI-900
• Practice with Azure services using a free account to gain hands-on experience
• Take practice tests to familiarize yourself with the exam format and question types
• Review Microsoft's AI documentation and case studies
• Aim for a score of 95% or higher in practice tests to ensure a comfortable margin for passing the actual exam

Conclusion

The AI-900 certification is an excellent starting point for those interested in AI and its implementation on Microsoft Azure. It validates your foundational knowledge of AI concepts and Azure AI services. This certification can be valuable for IT professionals, developers, or anyone looking to demonstrate their understanding of AI fundamentals in a Microsoft Azure context, regardless of their technical background.

Remember to always check the official Microsoft certification page for the most up-to-date information on exam content, structure, and preparation resources.