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 Duration 14 hours

Course Outline

Azure Machine Learning Fundamentals

  • Introduction to AML features and architectural design
  • Understanding end-to-end workflows via Azure ML pipelines
  • Navigating the Azure Machine Learning Studio interface

Data Preparation and Modeling

  • Data preprocessing and preparation
  • Model construction
  • Training and testing procedures

Model Evaluation and Robustness

  • Applying validation metrics to ML models
  • Strategies for handling and preventing overfitting

Model Management and Deployment

  • Registering trained models
  • Creating model images
  • Deployment strategies

OpenAI API Basics on Azure

  • Overview of the OpenAI API
  • Configuring API settings and authentication

Retrieval and Application Integration

  • Managing documents with AI Search
  • Integrating OpenAI models into existing applications

Customization and Production Practices

  • Model fine-tuning and customization techniques
  • Best practices for production environments

Summary and Next Steps

Requirements

  • Familiarity with Python and fundamental machine learning principles
  • Practical experience with REST APIs or SDKs
  • Basic knowledge of Azure services

Target Audience

  • Data scientists and ML engineers
  • Application developers implementing AI features
  • Technical leads and solution architects

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