This learning path delves into the end-to-end process of building and managing machine learning (ML) pipelines using OpenShift AI. Through a highly structured guide, developers and platform engineers are led through each step required to construct an efficient pipeline. Beginning with data acquisition, the pipeline navigates seamlessly through model training, and performance evaluation, then culminates in the storage of the trained model in Amazon S3. Furthermore, this learning path empowers developers to automate pipeline runs, which streamlines the entire ML workflow. 

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