Microsoft Azure AI Fundamentals (AI-900) Practice Exam

Which component in Azure Machine Learning is primarily responsible for data manipulation and transformation?

1. Module

2. Dataset

3. Pipeline

4. Service

The correct answer is: Module

The component in Azure Machine Learning that is primarily responsible for data manipulation and transformation is the module. Modules are building blocks within the Azure Machine Learning workspace that allow users to perform specific operations on data, including data cleaning, transformation, and processing tasks. Modules include various functionalities, such as data wrangling, feature engineering, and data preprocessing, which are essential for preparing the data in a way that it can be effectively used for training machine learning models. By utilizing modules, data scientists can clean and manipulate datasets to enhance the quality of information used in their models, ultimately leading to better performance and accuracy. In contrast, datasets serve as structured collections of data that Azure Machine Learning uses in experiments and model training but do not possess manipulation capabilities on their own. Pipelines, on the other hand, orchestrate a series of modules and automate the workflow but do not directly transform data themselves. Services in Azure typically refer to deployed machine learning models or other Azure services that provide functionality beyond data transformation.