In this blog, I talk about how I passed the Microsoft Certified: Azure AI Fundamentals AI-900 as a non-technical professional in under two weeks. So let me share some personal tips to help you nail these domains.
Think of this as a chat over coffee where I’m spilling all the secrets that worked for me. The AI-900 is beginner-friendly, but it’s got a lot of ground to cover, so let’s break it down domain by domain. Read through to know more about my experience and the resources and strategies I used to ace it.
The First Win: The Microsoft Voucher
When I won the Microsoft AI fest voucher, I thought I was halfway there. I did the Agentic AI challenge, and it did relate to the AI-900 syllabus, and I did not miss out on the Microsoft learn modules.
Breaking down every domain into smaller chunks to conquer it
Fun fact: okay, it does say “ describe” and when you dive deep in the study guide, you can also find some “identify.” Take this as a comforting factor, as it is easier to “ describe” and “identify” than to “implement” or “deploy.”
1. Describe Artificial Intelligence workloads and considerations (15–20%)
This domain is all about understanding what AI can do and the big-picture stuff like ethics, 
cost, and planning. You’ll need to know how AI fits into real-world scenarios and Microsoft’s responsible AI principles (fairness, accountability, transparency, etc.). I spent a weekend binge-reading this to get comfy with terms like “anomaly detection” or “knowledge mining.”
Focus on Responsible AI: Microsoft loves its ethical AI principles. learn the six principles
Real-World Examples: The exam throws scenario-based questions, like “A company wants to predict sales—what’s the workload?” (Answer: Machine Learning). I practiced by imagining AI in my daily life, like how Spotify’s song recommendations use ML or how chatbots on websites use conversational AI.
2. Describe Fundamental Principles of Machine Learning on Azure (15–20%)
You need to know the types of ML (supervised, unsupervised, reinforcement), key concepts (training vs. validation datasets), and Azure tools like Azure Machine Learning Studio and AutoML. I used Whizlabs AI-900 questions to test these.
3. Describe Features of Computer Vision Workloads on Azure (15–20%)
This covers how AI “sees” images and videos using Azure services like Computer Vision, Custom Vision, and Face API. Think object detection, facial recognition, or reading text in images (OCR).
Scenario-Based Practice: The exam might ask, “What service identifies text in a scanned receipt?” (Answer: Computer Vision with OCR). I practiced by thinking of use cases—like “a store sorting product images” (Custom Vision) or “security checking faces” (Face API). You don’t need to know how these services work under the hood. Just know what they do and when to use them.
4. Describe Features of Natural Language Processing (NLP) Workloads on Azure (15–20%)
You’ll cover Azure services like Language, Speech, Translator, and Bot Framework for tasks like sentiment analysis, speech-to-text, or chatbots.
Play with Demos: Try Azure’s Speech or Translator demos online. I used Translator to convert my grocery list to French—it’s silly but memorable. For Speech, I tested text-to-speech with funny phrases to hear how natural it sounds.
I got a question on “what service extracts key phrases from customer feedback?” (Answer: Azure Language).
5. Describe Features of Generative AI Workloads on Azure (15-20%)
- Generative AI uses Azure OpenAI Service and other Azure AI services to generate new content, such as text, images, or code. Consider the text generation model based on ChatGPT, the generation of images based on prompts, or the summary of documents.
- Generative AI is the part of it that is making something (new text, images), whereas NLP is the part that is understanding something (sentiment, translation), in case you got lost.
Pro Tip: Generative AI is trending, so expect 5–7 questions. I saw DALL-E all over the place.
My background and the resources I used
I do have a little tech background with my computer applications degree. I do not have any Azure experience at hand. I used my Whizlabs subscription and Microsoft Learn path to revise and used Copilot to make flashcards.
- As I already have my Whizlabs subscription, I made the most out of it, from Video courses to labs.
- I got my basics right, and after each video course I completed, I took that module’s
Practice test. And I just played around with the Hands-on labs and a bit of sandbox exploration.
Bonus Story: I bombed my first practice test (50%) and panicked. But after focusing on weak areas (NLP and generative AI). You’ll get there—just keep at it!
How I Stayed Calm and Beat Exam Anxiety
Being prepared is important. I began my studies not late and divided the material into small parts. This creates confidence and eliminates last-minute stress.
Time management: I have been taking timed mock exams to make myself feel more comfortable with the time. The test consists of 45 questions within 45 minutes. I bookmarked the difficult questions and returned to them later—do not get stagnated. Practice exams helped me keep up with the pace.
Hands-on training: Play with Computer Vision, Speech, or ML Studio. I learned more from 30 minutes of clicking around than hours of reading.
Practice Tests: I used Whizlabs practice exams. Don’t miss out on these.
Stay Calm: I freaked out seeing a question I didn’t know, but most are common sense if you’ve studied. Read carefully; some answers can seem close but wrong (For instance, picking “Computer Vision” instead of “Custom Vision”).
Schedule Smart: Book your exam when you’re hitting 85 %+ on practice tests. I took mine in the night, so I prepared the whole day —it helped me focus.
My go-to suggestions if you’re aiming to pass with flying colors.
If you are a tech newbie like me:
You’ve got this! The AI-900 is like learning the ABCs of Azure AI—it’s foundational; do not worry, it is not rocket science. Treat each domain like a mini-adventure, get hands-on experience to make it fun, and lean on practice tests to build confidence. If I can pass while juggling a job, you can too.
If you are an experienced professional: If you are 1, 2, or more than 3 years down the line, you can take the AI-102( a bit more challenging than the AI-900), or if you wish to begin from the fundamentals, it can look like a piece of cake. We do suggest that you get the basics right from your preparation.
The Final Win: Passing the AI-900.
Despite all the prep, I was low-key anxious, and it felt inevitable. I knew what it was like to pass, but the moment the screen popped, “Congrats, you passed the AI-900.” I knew it was all worth it.
Conclusion
As I read, to sum up my preparation, I got my basics right and tested more and more, finishing with the much-needed reassurance: Hands-on labs and Sandboxes. I’ve blogged about cloud certs on videos, but passing it is surreal. Hit me up when you crush that exam! Good luck, fellow learner!
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