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Duration 14 hours
Course Outline
Azure Machine Learning Core Concepts
- Exploration of AML features and architectural design
- Understanding end-to-end workflows in AML (Azure ML pipelines)
- Interface navigation within Azure Machine Learning Studio
Data Handling and Model Development
- Techniques for data preparation
- Constructing a machine learning model
- Processes for training and testing the model
Model Assessment and Stability
- Selecting validation metrics for ML models
- Strategies for detecting and preventing overfitting
Model Lifecycle and Release
- Registering trained models in the registry
- Generating model container images
- Executing model deployment
Azure OpenAI API Essentials
- Introduction to the OpenAI API landscape
- Configuring API settings and authentication protocols
Retrieval Systems and App Integration
- Managing documents via AI Search
- Incorporating OpenAI models into application logic
Specialization and Production Readiness
- Techniques for model fine-tuning and customization
- Implementing best practices for production environments
Course Wrap-up and Future Directions
Requirements
- Proficiency in Python and foundational knowledge of machine learning principles
- Practical experience with REST APIs or SDKs
- General familiarity with the Azure service ecosystem
Target Audience
- Data scientists and ML engineers
- Application developers integrating AI capabilities
- Technical leads and solution architects
