AI Concepts & Capabilities
This domain covers 40-45% of the AI-901 exam. You'll learn to identify AI workloads, responsible AI principles, types of machine learning, generative AI concepts, computer vision fundamentals, text analytics, and when to use which Azure AI service category.
Challenges in this domain
| # | Challenge | Key topics |
|---|---|---|
| 01 | Identify AI Workloads | Computer vision, NLP, speech, document intelligence, generative AI |
| 02 | Responsible AI Principles | Fairness, reliability, privacy, inclusiveness, transparency, accountability |
| 03 | Common AI Patterns and Use Cases | When to use which AI workload, real-world scenarios |
| 04 | Azure AI Services Overview | Service categories, pricing, multi-service vs single-service |
| 05 | Regression in Machine Learning | Supervised learning, features vs labels, predicting numeric values |
| 06 | Classification in Machine Learning | Binary vs multi-class, precision/recall, evaluation metrics |
| 07 | Clustering in Machine Learning | Unsupervised learning, K-Means, customer segmentation |
| 08 | Deep Learning and Transformers | Neural networks, CNNs, attention mechanism, GPT/BERT |
| 09 | Azure Machine Learning Workspace | AutoML, Designer, compute, endpoints, model registry |