According to the Microsoft Azure AI Fundamentals (AI-900) curriculum and Microsoft Learn’s “Explore Automated Machine Learning in Azure Machine Learning” module, Automated ML (AutoML) is the Azure Machine Learning capability that allows users to quickly build, train, and deploy predictive models with minimal or no coding experience.
Automated ML automatically performs tasks that would normally require expert data science knowledge, such as:
Selecting appropriate algorithms (e.g., decision trees, logistic regression, random forests)
Performing hyperparameter tuning to optimize model accuracy
Handling missing data and feature scaling automatically
Generating performance metrics and best model recommendations
This feature is especially useful for business analysts, developers, or beginners who want to leverage machine learning for predictions (like sales forecasting, churn analysis, or demand prediction) without having to write complex Python code.
Other options explained:
A. ML pipelines automate and organize workflows for model training and deployment but still require pre-built models.
B. Copilot is an AI-powered assistant embedded in Microsoft tools for productivity, not a model training feature.
C. DALL-E is an image generation model under Azure OpenAI, not a predictive modeling tool.
Thus, per official Microsoft Learn content, Automated Machine Learning is the correct capability to quickly build and deploy predictive models with minimal coding.
