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Duration 14 hours
Course Outline
Fundamentals of Azure Machine Learning
- Core features and architectural overview of AML
- Understanding end-to-end workflows within AML (Azure ML pipelines)
- Navigation and usage of Azure Machine Learning Studio
Data Preparation and Modeling
- Preprocessing and preparing data
- Constructing machine learning models
- Model training and testing processes
Model Evaluation and Robustness
- Applying validation metrics to ML models
- Strategies for managing and preventing overfitting
Model Management and Deployment
- Registering trained models
- Building model images
- Deploying models to production
Foundations of the OpenAI API on Azure
- Introduction to the OpenAI API
- Configuring APIs and handling authentication
Retrieval and Application Integration
- Managing documents with AI Search
- Integrating OpenAI models into application stacks
Customization and Production Best Practices
- Model fine-tuning and customization
- Best practices for production environments
Conclusion and Next Steps
Requirements
- Proficiency in Python and foundational machine learning concepts
- Practical experience with REST APIs or SDKs
- General knowledge of Azure services
Target Audience
- Data scientists and ML engineers
- Application developers implementing AI features
- Technical leads and solution architects
