Test & Debug Java ML Pipelines

This advanced course guides learners through testing and debugging Java-based ML pipelines using professional-grade tools and CI/CD workflows. You’ll write robust unit and integration tests for core ML components like EntropyCalculator and Normalizer, apply Mockito to mock file I/O, and increase test coverage from 62% to 85%. Learners will trace intermittent pipeline failures, diagnose random seed issues, and implement reproducibility (new Random(42)) to ensure stability across multiple runs. The course concludes with CI-based automation using JUnit, Tribuo, and GitHub Actions, preparing parti…