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Duration 14 hours
Course Outline
Core Azure Machine Learning Concepts
- Introduction to AML capabilities and architectural design
- Walkthrough of a complete workflow within AML (Azure ML pipelines)
- Getting comfortable with the Azure Machine Learning Studio interface
Data Handling and Model Construction
- Processes for data preparation
- Techniques for building a model
- Strategies for training and testing models
Evaluating Model Performance and Stability
- Applying validation metrics to ML models
- Mitigating and preventing overfitting issues
Managing and Deploying Models
- Procedure for registering a trained model
- Generating a model image
- Execution of model deployment
Foundations of the OpenAI API on Azure
- Getting started with the OpenAI API
- Setting up API configuration and handling authentication
Retrieval Mechanisms and App Integration
- Utilizing documents with AI Search
- Embedding OpenAI models into application logic
Advanced Customization and Production Standards
- Model fine-tuning and customization methods
- Adhering to best practices in production environments
Course Summary and Future Pathways
Requirements
- Working knowledge of Python and fundamental machine learning principles
- Proficiency with REST APIs or SDKs
- Basic acquaintance with Azure service offerings
Target Audience
- Data scientists and ML engineers
- Application developers implementing AI functionalities
- Technical leaders and solution architects
