AI-102 Study Plan
Why AI-102?
As someone with some experience in Python and machine learning—and not having dipped my toes into Azure’s AI offerings—the AI-102: Designing and Implementing an Azure AI Solution certification felt like the perfect next step for me. I’ve spent time building models, tuning hyperparameters, and enjoyed deploying ML systems as part of my AI Certification from U of T—but I’ve yet to fully explore how Microsoft Azure delivers AI capabilities at scale.
In this post, I’ll share why I chose AI-102, how it fits into my broader goals, and what my study plan looks like.
The AI-102 exam is ideal for developers and ML practitioners who want to design and implement AI solutions using Azure’s prebuilt services. It covers:
- Azure Cognitive Services (vision, speech, language)
- Conversational AI with Azure Bot Service
- AI security and cost governance
- Best practices for deploying AI at scale in the cloud
My goal is to understand how to build production-ready AI applications using Azure. I'm hoping that doing the AI-102 certification will give me exposure to practical, real-world use cases like OCR, chatbot development, text analytics, and speech recognition—all the while, getting a deeper understanding of a major cloud player's AI portfolio and all the nuances that it can come with.
🤔 Why Not Just Stick with DP-100?
That’s a question I asked myself since it aligns more with my experience with the AI Certification from U of T.
The DP-100 exam is more about data science and building models using Azure Machine Learning—something I already have some academic experience with. I want AI-102 to complement my ML knowledge by giving me the cloud integration and deployment skills I currently lack.
📅 My Study Plan
I’m aiming to take the exam as soon as possible. With 2–4 hours per week, I asked ChatGPT to create me a 15-week plan that touches every major topic on the exam:
as I follow along an official guide, I'll get to proof read and make this part more accurate but I'll go with this for now
| Week | Focus Area |
|---|---|
| Week 1 | Azure AI Overview + Setting Up Account |
| Week 2–3 | Cognitive Services + Resource Management |
| Week 4–5 | Computer Vision |
| Week 6–7 | Natural Language Processing |
| Week 8 | Speech Recognition and Synthesis |
| Week 9 | Conversational AI with Bot Service |
| Week 10 | Security and Responsible AI |
| Week 11–12 | Practice Exams and Flashcards |
| Week 13–14 | Mock Exam + Fill Knowledge Gaps |
| Week 15 | Final Review + Exam Day! |
I plan on sharing blog posts along the way to track my progress and share what I learn—successes, challenges, and all. (I've already started studying on MSFT Learn so there will be a new one soon 🤞)
✍️ What’s Next?
Once I've built something fun (or learnt about something that will lead to building something fun), I'll blog about it. For now, wish me luck 🙏
Let’s Connect
Are you also preparing for AI-102 or exploring Azure’s AI capabilities? I’d love to hear how you're approaching your study plan—or what you're building with Azure AI. Feel free to connect with me on LinkedIn.
Thanks for reading!
This post was created with the assistance of an AI tool (ChatGPT) to support drafting and structure. Final content has been reviewed and edited by me.