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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Overview of AML capabilities and architectural design
- Understanding the end-to-end process within AML (including Azure ML pipelines)
- Guided navigation of the Azure Machine Learning Studio interface
Data Handling and Model Construction
- Preparing data for analysis
- Structuring and building models
- Conducting model training and testing cycles
Assessing Model Quality and Stability
- Applying validation metrics to ML models
- Mitigating and preventing overfitting
Managing and Releasing Models
- Registering trained models for reuse
- Generating model images
- Executing model deployment tasks
Basics of the OpenAI API on Azure
- Getting started with the OpenAI API
- Setting up API configuration and secure authentication
Search Integration and Application Embedding
- Leveraging AI Search for document retrieval
- Embedding OpenAI models into application logic
Customization and Production Standards
- Performing model fine-tuning and customization
- Adhering to best practices for production environments
Recap and Future Directions
Requirements
- Familiarity with Python and fundamental machine learning principles
- Practical experience working with REST APIs or SDKs
- Foundational knowledge of Azure services
Target Audience
- Data scientists and ML engineers
- Application developers implementing AI features
- Technical leaders and solution architects
