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Duration 14 hours
Course Outline
Azure Machine Learning Fundamentals
- Overview of AML features and architecture
- Understanding end-to-end workflows in AML (Azure ML pipelines)
- Navigation and utilization of Azure Machine Learning Studio
Data Preparation and Modeling
- Techniques for data preparation
- Process of building a model
- Training and testing model performance
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
- Executing model deployment
OpenAI API Basics on Azure
- Introduction to the OpenAI API
- Configuring APIs and managing authentication
Retrieval and Application Integration
- Working with documents using AI Search
- Integrating OpenAI models into applications
Customization and Production Practices
- Model fine-tuning and customization techniques
- Adhering to best practices in production environments
Summary and Next Steps
Requirements
- A solid grasp of Python and fundamental machine learning concepts
- Practical experience working with REST APIs or SDKs
- Basic familiarity with the Azure service ecosystem
Target Audience
- Data scientists and ML engineers
- Application developers implementing AI features
- Technical leads and solution architects
