Introduction
Whatsup everyone? This blog is about Microsoft’s certificate “Azure AI Fundamentals”, which is also referred to as AI 900, which is the certificate code. This is a fundamental certificate that helps the candidate demonstrate understanding and knowledge related to Machine Learning and AI, and all the Microsoft Azure’s services and tools about the topic. The following is the link to Microsoft Learn’s page to know the most updated information about it.
Microsoft Certified: Azure AI Fundamentals – Certifications
Topics that it covers
The certificate covers the following topics:
Artificial Intelligence workloads and considerations
Includes a brief introduction to Computer Vision workloads, Natural Language Processing Workloads, Document Processing Workloads, and GenAI Workloads. Further, it discusses about principles of responsible AI.
Fundamental principles of Machine Learning on Azure
This section talks about various types of Machine Learning, such as Regression, Classification, Clustering, Deep Learning, and Transformer Architecture. Later on, it also teaches how to use Azure tools and services to create ML models.
Computer Vision workloads on Azure
Computer Vision modules introduce various Computer Vision solutions like Image Classification, Object Detection, Optical Character Recognition, and Facial Detection and Analysis. Again, moving forward, it demonstrates how to leverage Azure to implement these services.
Natural Language Processing (NLP) workloads on Azure
In this section, various features of Natural Language Processing are introduced, such as Key Phrase Extraction, Entity Recognition, Sentiment Analysis, Language Modeling, Speech Recognition and Synthesis, and Translation. Additionally, walks through the documentation that helps the user set up all these services using Azure.
Generative AI workloads on Azure
As the name suggests, this section introduces Generative AI workloads on Azure, including its features, scenarios, and considerations, and all the tools provided by Azure in this vertical.
How did I prepare for it?
To prepare for the exam, I followed all the modules described in Microsoft Learn.
Introduction to AI in Azure – Training
I went through all the units in each module, read, and tried understanding all the topics while making sure to get some hands-on experience, as included in the above-mentioned learning path, which gave me more exposure to all the services and tools discussed in the units. Meanwhile, I also wrote notes that try to explain all the topics in simpler terms.
Alternatively, you can buy any Udemy course or follow a FreeCodeCamp video, as per your capacity. Nonetheless, I feel the material provided by Microsoft Learn is good enough.
Note: There are a couple of places in my notes where I added a detailed explanation of the topic, which might be out of scope for the certification. I researched the content for my understanding and later decided to keep it in my notes so it’s easy for me to understand it while I revise, and might also help others.
I would also recommend that you go through all the units in the modules while also making your own notes to help you revise them.
Recommendation: As a suggestion, try understanding all the topics fundamentally, even if it’s not required to pass the exam. The reason behind doing this is that once you understand it from the foundation, it will be stored in your memory, and you will not have to revise it again and again.
How did I revise?
Once you are done with all the units in all the modules, I would suggest that you go ahead and book the test. After booking, you will have a fixed amount of time to revise everything. Following is how I used to revise for the exam, after booking the test.
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Microsoft Learn provides the practice tests that you can take to simulate the exam environment.
Microsoft Certified: Azure AI Fundamentals – Certifications
The best thing about these practice tests is that at the end of each test, along with the score, it gives you the list of modules in which you performed poorly and need to revise. This feature helped me evaluate the modules where I was lacking, so I could focus specifically on those, not everything. I would give one practice test daily and revisit my notes according to the list of modules provided.
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Before 1-2 days of the exam, I would suggest that you go through some external websites that provide sample exam questions, such as Tutorial Dojo, Exam Pro, etc. Try solving these sample questions. This helps you get fully prepared for your test.
How did I appear for the exam?
Talking about booking the exam, it costs USD 99. To get a discount, I would recommend that you go to Microsoft Virtual Training Days, browse for AI 900, and enroll for the training day as per your convenience. Once you complete these virtual training day sessions, you will automatically get a 50% discount on the exam fees.
Note: This discount percentage or availability might vary in the future as decided by Microsoft.
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As for the exam mode, you can take the exam from home or go to a testing center. I preferred going to a testing center rather than clearing everything off my desk and background. Also, since this was my first certification exam, it made more sense to take it at a testing center.
Conclusion
To conclude the blog, the material not only talks about services and tools offered by Azure, but also teaches lots of fundamental concepts related to AI and ML. Hence, this can be a stepping stone, especially if you want to transition into AI and ML. This certificate may help you establish your credibility, which in turn can help you get that opportunity that you have been looking for.
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Also, I hope you understand that this is a fundamental-level certificate, so you still need to do a lot of work and learning. Thus, have a next step ready for yourself after this. Best of Luck!!
Disclaimer:
Please note that the content and structure of this certification may change in the future. Microsoft Learn can update the modules, add or remove topics, or change how the exam is evaluated. The information shared in this blog is based on what was available at the time I prepared for the exam.