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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Introduction to AML capabilities and architectural design
- Understanding end-to-end processes within AML (Azure ML pipelines)
- Mastering the interface of Azure Machine Learning Studio
Data Handling and Model Development
- Data curation and preparation
- Constructing machine learning models
- Model training and testing procedures
Model Assessment and Stability
- Selecting validation metrics for ML models
- Strategies for managing and preventing overfitting
Model Lifecycle and Deployment
- Registering trained models
- Generating model images
- Executing model deployments
Basics of the OpenAI API on Azure
- Getting started with the OpenAI API
- Configuring APIs and managing authentication
Retrieval Capabilities and Application Integration
- Managing documents via AI Search
- Incorporating OpenAI models into application architecture
Customization and Production Readiness
- Techniques for model fine-tuning and customization
- Best practices for production environments
Conclusion and Future Directions
Requirements
- Solid grasp of Python and fundamental machine learning principles
- Practical experience with REST APIs or SDKs
- Foundational knowledge of Azure services
Target Audience
- Data scientists and ML engineers
- Application developers implementing AI capabilities
- Technical leads and solution architects
