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AI-900: Building ML Pipelines in Azure with Datasets, Computes and Modules

Azure Machine Learning designer provides a visual interface to construct end-to-end ML workflows. Learn how key components like datasets, computes and modules can be dragged onto the canvas.


Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. dataset
B. compute
C. pipeline
D. module


A. dataset
D. module


You can drag-and-drop datasets and modules onto the canvas.

The correct answer is A and D. You can drag both datasets and modules onto a canvas in Azure Machine Learning designer.

A dataset is a data asset that you can use as an input or output for a component in a pipeline. You can create a dataset from various data sources, such as Azure Blob Storage, Azure Data Lake Storage, Azure SQL, or local files. You can also register a dataset in your workspace and access it from the asset library in the designer. A dataset can only connect to a component, not to another dataset.

A module is a component that performs a specific machine learning task, such as data transformation, feature engineering, model training, model evaluation, or model deployment. You can use the built-in modules provided by Azure Machine Learning, or create your own custom modules using Python or R code. You can also share and reuse modules across different pipelines and workspaces. A module can connect to either a dataset or another module, depending on its input and output specifications.

A compute is a cloud resource that you can use to run your pipeline jobs. You can configure a compute target for each pipeline draft in the designer. You can also create and manage compute targets from the Azure Machine Learning studio. A compute is not a component that you can drag onto a canvas.

A pipeline is a workflow of connected components that defines the steps of your machine learning project. You can create a pipeline visually by dragging and dropping components onto a canvas in the designer. You can also edit, run, and publish pipelines from the designer. A pipeline is not a component that you can drag onto a canvas, but rather the result of connecting components.


Microsoft Docs > Azure > Machine Learning > What is Azure Machine Learning designer?

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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