Trainer References for March 2025
Table of contents
- Trainer References for March 2025
- Learning Path 1: Introduction to AI and AI on Azure
- Learning Path 2: Develop computer vision solutions with Azure AI Vision
- Learning Path 3: Develop natural language processing solutions
- Learning Path 4: Develop Generative AI Solutions with Azure OpenAI Service
- Learning Path 5: Creating a Knowledge Mining Solution
- Learning Path 6: Develop solutions with Azure AI Document Intelligence
Learning Path 1: Introduction to AI and AI on Azure
| Lessons | Notes |
|---|---|
| AI on Azure | - Responsible AI practices - Azure Machine Learning - Azure AI Search - What is the Azure Developer CLI? |
| Get started with Azure AI services | - Azure AI services REST API reference - Overview of the Azure AI SDKs |
| Using Azure AI Services for enterprise applications | - SQL to Kusto Query Language cheat sheet - What are Azure AI containers? - Microsoft Artifact Registry |
Learning Path 2: Develop computer vision solutions with Azure AI Vision
| Lessons | Notes |
|---|---|
| Analyze and manipulate images | - Enhance your apps with Azure AI Vision - Call the Image Analysis 4.0 Analyze API - Image captions (version 4.0) - OCR - Optical Character Recognition |
| Detecting Faces with the Azure AI Vision | - Limited Access features for Azure AI services |
| Custom vision models with Azure AI Custom Vision | - Create a custom Image Analysis model |
| Analyze video | - Azure AI Video Indexer |
Learning Path 3: Develop natural language processing solutions
| Lessons | Notes |
|---|---|
| Analyzing text | - What is Azure AI Language? - Natural language processing technology - Supported Named Entity Recognition (NER) entity categories and entity types - Supported Personally Identifiable Information (PII) entity categories |
| Translating text | - Translator 3.0: Translate - Text Translation REST API - How to receive word alignment information - Add profanity filtering with Translator |
| Build a question answering solution | - Enrich your project with active learning |
| Build a conversational language understanding app | - What is Azure AI Language? - Natural language processing technology - Supported prebuilt entity components - Evaluation metrics for conversational language understanding models |
| Custom classification and named entity extraction | - - |
| Speech recognition, synthesis, and translation | - Speech to text REST API - Batch synthesis API for text to speech - SpeechSynthesisOutputFormat Enum - Language and voice support for the Speech service |
Learning Path 4: Develop Generative AI Solutions with Azure OpenAI Service
| Lessons | Notes |
|---|---|
| Get started with Azure OpenAI Service | - Standard deployment model availability - Azure OpenAI Service models - Tokenizer - Open AI platform - Azure Status - OpenAI Status |
| Develop apps with Azure OpenAI Service | - Azure OpenAI Service REST API reference - OpenAI text generation models |
| Apply prompt engineering with Azure OpenAI Service | - Introduction to prompt engineering |
| Use your own data with Azure OpenAI Service | - Azure OpenAI On Your Data - Azure OpenAI On Your Data API Reference - Sample code for a simple web chat experience through Azure OpenAI, including Azure OpenAI On Your Data. |
Learning Path 5: Creating a Knowledge Mining Solution
| Lessons | Notes |
|---|---|
| Implementing an Intelligent Search Solution | - Integrated data chunking and embedding in Azure AI Search - AI enrichment in Azure AI Search - Tips for AI enrichment in Azure AI Search |
| Create a custom skill for Azure AI Search | - - |
| Creating a Knowledge Store | - Define projections in a knowledge store |
Learning Path 6: Develop solutions with Azure AI Document Intelligence
| Lessons | Notes |
|---|---|
| Use prebuilt Document Intelligence models | - Document processing models - Use Document Intelligence models |
| Train a custom Document Intelligence model | - - |