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Duration 14 hours
Course Outline
Azure Machine Learning Fundamentals
- Introduction to AML features and architectural design
- Understanding end-to-end workflows via Azure ML pipelines
- Navigating the Azure Machine Learning Studio interface
Data Preparation and Modeling
- Data preprocessing and preparation
- Model construction
- Training and testing procedures
Model Evaluation and Robustness
- Applying validation metrics to ML models
- Strategies for handling and preventing overfitting
Model Management and Deployment
- Registering trained models
- Creating model images
- Deployment strategies
OpenAI API Basics on Azure
- Overview of the OpenAI API
- Configuring API settings and authentication
Retrieval and Application Integration
- Managing documents with AI Search
- Integrating OpenAI models into existing applications
Customization and Production Practices
- Model fine-tuning and customization techniques
- Best practices for production environments
Summary and Next Steps
Requirements
- Familiarity with Python and fundamental machine learning principles
- Practical experience with REST APIs or SDKs
- Basic knowledge of Azure services
Target Audience
- Data scientists and ML engineers
- Application developers implementing AI features
- Technical leads and solution architects