The correct answers are A. Use a graphical user interface (GUI) to run automated machine learning experiments and C. Use a graphical user interface (GUI) to define and run machine learning experiments from Azure Machine Learning designer.
According to the Microsoft Azure AI Fundamentals (AI-900) official documentation and Microsoft Learn module "Create and manage Azure Machine Learning workspaces", there are two workspace tiers: Basic and Enterprise. The Enterprise workspace provides advanced capabilities for automation, visualization, and collaboration that are not available in the Basic tier.
Specifically:
* Automated machine learning (AutoML) using a GUI is only available in the Enterprise tier. AutoML automatically selects algorithms and tunes hyperparameters through the Azure Machine Learning studio interface.
* Azure Machine Learning designer, which allows users to visually drag and drop datasets and modules to create machine learning pipelines, also requires the Enterprise workspace.
In contrast:
* B. Create a compute instance and D. Create a dataset from a CSV file are fundamental actions supported in both Basic and Enterprise workspaces. These do not require the advanced licensing features of the Enterprise edition.
Therefore, tasks involving the graphical, no-code tools-Automated ML (AutoML) and the Designer- require the Enterprise workspace, aligning with AI-900's learning objectives.
Reference:Microsoft Learn - Create and manage Azure Machine Learning workspaces and Automate model training with Azure Machine Learning