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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Introduction to AML features and architectural design
- Understanding end-to-end workflows in AML (Azure ML pipelines)
- Interface navigation in Azure Machine Learning Studio
Data Preparation and Model Construction
- Techniques for data preparation
- Model architecture and building
- Model training and testing procedures
Model Assessment and Robustness
- Applying validation metrics to ML models
- Strategies for detecting and preventing overfitting
Model Lifecycle Management and Deployment
- Registering trained models
- Generating model images
- Executing model deployment
Basics of OpenAI API on Azure
- Overview of the OpenAI API
- API setup and authentication protocols
Retrieval Strategies and Application Integration
- Managing documents with AI Search
- Embedding OpenAI models into applications
Customization and Production Standards
- Model fine-tuning and customization techniques
- Best practices for production environments
Conclusion and Future Directions
Requirements
- Proficiency in Python and foundational machine learning concepts
- Experience working with REST APIs or SDKs
- Basic knowledge of Azure services
Intended Audience
- Data scientists and ML engineers
- Application developers implementing AI capabilities
- Technical leads and solution architects
