Explanation:
The question asks which three tasks can be performed in an Azure Machine Learning Basic edition workspace. Based on the community discussion and Azure ML documentation, the Basic edition supports: A) Creating a Compute Instance to run code in Jupyter notebooks, which is a core development feature; C) Using the designer to train models via drag-and-drop modules, as the designer is available in Basic edition; and E) Using the Automated ML user interface for model training, which is also supported in Basic edition. Option B (Create an AKS inference cluster) is incorrect because AKS deployment requires the Enterprise edition (now retired, but Basic does not support advanced compute like AKS clusters). Option D (Create a versioned tabular dataset) is incorrect as dataset versioning is an Enterprise feature, not available in Basic edition. The community consensus, with high upvotes for ACE (80%), confirms this, and recent comments (e.g., December 2023) align with Azure ML capabilities, noting that AKS and versioned datasets are not supported in Basic edition.
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You are planning to provision an Azure Machine Learning Basic edition workspace for a data science project. You need to identify which tasks can be performed in this workspace.
Which three tasks can be performed? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
A
Create a Compute Instance and use it to run code in Jupyter notebooks.
B
Create an Azure Kubernetes Service (AKS) inference cluster.
C
Use the designer to train a model by dragging and dropping pre-defined modules.
D
Create a tabular dataset that supports versioning.
E
Use the Automated Machine Learning user interface to train a model.
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