Here is some additional information to help you solidify your knowledge and prepare for the AI-900 exam.
1. Core AI Approaches
| AI Approach | What It’s Best At |
|---|
| Traditional (Rule-Based) AI | Fixed logic, deterministic decisions |
| Predictive Machine Learning | Predicting values or classifying outcomes |
| Generative AI | Creating new content from prompts |
Another way to relay the same information:
- If it follows rules, it’s traditional AI.
- If it predicts, it’s ML.
- If it creates, it’s generative AI
2. Scenario-to-Approach Mapping
Business Rules & Automation
| Scenario | Correct AI Approach | Why |
|---|
| Approve a loan if income > threshold | Traditional AI | Rule-based, no learning required |
| Route support tickets based on keywords | Traditional AI | Deterministic logic |
| Enforce compliance policies | Traditional AI | Rules must be followed exactly |
Predictive & Analytical Scenarios
| Scenario | Correct AI Approach | Why |
|---|
| Predict customer churn | Predictive ML (Classification) | Binary outcome |
| Forecast product demand | Predictive ML (Regression) | Numeric prediction |
| Detect credit card fraud | Predictive ML (Classification) | Probability-based decision |
| Predict house prices | Predictive ML (Regression) | Continuous value |
| Segment customers | Predictive ML (Clustering) | Discover groups |
Natural Language Processing (NLP)
| Scenario | Correct AI Approach | Why |
|---|
| Analyze customer sentiment | Predictive ML (NLP) | Classification of sentiment |
| Extract key phrases from text | Predictive ML (NLP) | Pattern recognition |
| Recognize named entities | Predictive ML (NLP) | Identify structured info |
| Translate text | Generative AI / NLP | Generates new text |
| Summarize documents | Generative AI | Content creation |
Computer Vision
| Scenario | Correct AI Approach | Why |
|---|
| Identify objects in an image | Predictive ML (Vision) | Classification/detection |
| Detect faces in images | Predictive ML (Vision) | Pattern recognition |
| Read printed text from images (OCR) | Predictive ML (Vision) | Extraction task |
| Generate images from text | Generative AI | Creates new images |
Speech Workloads
| Scenario | Correct AI Approach | Why |
|---|
| Convert speech to text | Predictive ML (Speech) | Recognition task |
| Convert text to speech | Generative AI | Generates audio |
| Identify spoken language | Predictive ML | Classification |
Generative AI Scenarios
| Scenario | Correct AI Approach | Why |
|---|
| Generate an email from a prompt | Generative AI | New content |
| Write code from a description | Generative AI | Content generation |
| Answer questions conversationally | Generative AI | Dynamic responses |
| Create images from text prompts | Generative AI | Creative output |
3. Azure Service Mapping
| Scenario Type | Azure Service |
|---|
| Predictive ML | Azure Machine Learning |
| NLP (Sentiment, Entities) | Azure AI Language |
| Speech workloads | Azure AI Speech |
| Vision workloads | Azure AI Vision |
| Generative AI | Azure OpenAI Service |
| Rule-based workflows | Logic Apps / Power Automate |
4. Common AI-900 Exam Traps
| Trap | Correct Thinking |
|---|
| “Translation is classification” | ❌ Translation generates text |
| “Chatbots are always rule-based” | ❌ Modern chatbots use generative AI |
| “OCR generates text” | ❌ OCR extracts existing text |
| “Generative AI replaces ML” | ❌ Different goals |
Go to the AI-900 Exam Prep Hub main page.
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