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Duration 14 hours
Course Outline
Foundations of Azure Machine Learning
- Insight into AML features and architectural design
- Understanding end-to-end workflows within AML (Azure ML pipelines)
- Exploring the Azure Machine Learning Studio interface
Data Preparation and Model Development
- Techniques for data preparation
- Constructing a machine learning model
- Processes for training and testing the model
Model Assessment and Stability
- Applying validation metrics to ML models
- Strategies for handling and mitigating overfitting
Model Governance and Deployment
- Registering a completed trained model
- Generating a model image
- Executing model deployment
Azure OpenAI API Essentials
- Introduction to the OpenAI API ecosystem
- Configuring APIs and managing authentication
Retrieval and Application Integration
- Managing documents with AI Search
- Integrating OpenAI models into application architectures
Customization and Production Readiness
- Techniques for model fine-tuning and customization
- Implementing best practices in production environments
Conclusion and Future Pathways
Requirements
- Proficiency in Python and a foundational understanding of machine learning principles
- Familiarity with REST APIs or SDKs
- Basic knowledge of the Azure service ecosystem
Target Audience
- Data scientists and ML engineers
- Application developers integrating AI features
- Technical leads and solution architects
