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Course Outline
Azure Machine Learning Fundamentals
- Overview of AML features and architecture.
- Overview of an end-to-end workflow in AML (Azure ML pipelines).
- Navigating Azure Machine Learning Studio.
Data Preparation and Modeling
- Data preparation.
- Building a model.
- Training and testing a model.
Model Evaluation and Robustness
- Validation metrics for ML models.
- Handling and preventing overfitting.
Model Management and Deployment
- Registering a trained model.
- Creating a model image.
- Deploying a model.
OpenAI API Basics on Azure
- Introduction to the OpenAI API.
- API configuration and authentication.
Retrieval and Application Integration
- Documents with AI Search.
- Integrating OpenAI models into applications.
Customization and Production Practices
- Model fine-tuning / customization.
- Best practices in production.
Summary and Next Steps
Requirements
- Understanding of Python and basic machine learning concepts.
- Experience with REST APIs or SDKs.
- Basic familiarity with Azure services.
Audience
- Data scientists and ML engineers.
- Application developers building AI features.
- Technical leads and solution architects.
14 Hours
