Run model training scripts: Track model training with MLflow in a job run

Build evidence for this objective

Learn the concept across structured materials, then test it through adaptive questions and applied scenarios. Your results contribute to an objective-level mastery view and your next recommended action.

Official references

• Run training scripts and track models with MLflow in Azure Machine Learning
• Train and track machine learning models with MLflow in Microsoft Fabric
• Automate model training with GitHub Actions
• Introduction to using Managed Identity to authenticate to Azure OpenAI in Microsoft Foundry Models with .NET
• Get started with language models in Azure Databricks
• Evaluate language models with Azure Databricks
• Design and implement models and embeddings with SQL
• Streamline training plans with AI tools
• Design and implement data modeling with Azure Databricks
• Fine-tune language models with Azure Databricks