I Passed the Azure AI Fundamentals Certification Exam (AI-900) - Lessons Learned

I'm thrilled to announce that I recently passed the Microsoft Azure AI Fundamentals certification exam (AI-900)! It was a challenging but rewarding experience that taught me a ton about Azure's AI capabilities. In this blog post, I'll share some of the key lessons I learned while preparing that can help others studying for the AI-900.

Overview of the AI-900 Exam

The AI-900 exam covers a broad range of topics related to implementing Azure AI solutions. Some of the major domains include:

• Azure AI Fundamentals - Key concepts like machine learning, deep learning, computer vision, natural language processing, conversational AI, and responsible AI design

• Use Cognitive Services for vision, speech, language, decision, and search solutions

• Implement conversational AI solutions like chatbots using Azure Bot Service and Azure Cognitive Service pre-built bots

• Explore machine learning solutions like automated ML in Azure Machine Learning studio

• Implement computer vision solutions for image classification, object detection, face detection and recognition

• Learn how to monitor and manage responsible AI systems in Azure

My impression is that the exam thoroughly tests your knowledge across all these domains. You need both depth and breadth to pass.

Most Reliable Study Materials

Without a doubt, the Microsoft Learn modules and practice tests were the most authoritative and useful resources for the exam. I highly recommend working through all the suggested modules, taking detailed notes, and using the knowledge checks to validate understanding.

The modules can feel dry at times, so I supplemented them with John Savil's excellent AI-900 video course on YouTube. His demonstrations and explanations really helped the concepts click. I also watched a couple other AI-900 video courses for additional perspectives.

However, with the pace of change in Azure AI, make sure any video content you use is up-to-date, as Microsoft Learn is the source of truth.

Key Topic Areas to Study

Based on my experience, make sure you fully understand these key topics:

• Computer vision - Image classification, object detection, facial detection/recognition. Know the Cognitive Services like Computer Vision and Face API.

• Conversational AI - Chatbots, virtual assistants, pre-built bots. Understand basics of Azure Bot Service.

• Responsible AI - Monitoring for bias, interpreting results, gaining user trust. Tools like AI Fairness, Interpretability, and Explainability.

• Language - Sentiment analysis, language detection, translation. Services like Text Analytics and Translator.

• Speech - Speech-to-text, text-to-speech. Know the Speech service.

Also spend time with the AI ethics and responsible design concepts. This is an important theme across the exam.

Helpful Tips & Tricks

Here are some tips that helped me navigate tricky questions:

• Carefully read each question - key terms like "label", "bounding box", or "embedding" give hints.

• Taking detailed notes on Microsoft Learn is a must to connect concepts across modules.

• Some questions blend 3 sub-questions into one - watch for key phrases in each.

• Flag unsure questions to review later so you can focus on ones you know.

• The time limit felt sufficient to me, but pace yourself.

Conclusion

Passing this exam required dedication and hard work, but I found the preparation process hugely valuable for learning Azure AI capabilities. I hope these lessons from my experience help you on your journey to becoming a certified Azure AI Fundamentals expert! Let me know if you have any other questions.