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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Introduction to AML features and architecture
- Understanding the end-to-end workflow in AML (Azure ML pipelines)
- Navigating the Azure Machine Learning Studio interface
Data Processing and Model Development
- Preparing data for analysis
- Constructing machine learning models
- Training and testing model performance
Model Assessment and Reliability
- Applying validation metrics to ML models
- Mitigating and preventing overfitting issues
Model Governance and Deployment
- Registering trained models
- Generating model images
- Deploying models to production
Essentials of the OpenAI API on Azure
- Introduction to the OpenAI API
- Configuring APIs and managing authentication
Retrieval and Application Integration
- Utilizing documents with AI Search
- Embedding OpenAI models into application architectures
Customization and Production Standards
- Model fine-tuning and customization
- Adhering to best practices in production environments
Wrap-up and Future Pathways
Requirements
- Proficiency in Python and a foundational understanding of machine learning principles
- Practical experience with REST APIs or SDKs
- General familiarity with Azure services
Target Audience
- Data scientists and ML engineers
- Application developers focused on incorporating AI features
- Technical leads and solution architects
