Andrew Jones is a data engineer and ML educator focused on the unsexy but critical foundation of machine-learning work: the data preparation and cleaning craft that determines whether downstream models are even worth training.
His CourseFlix listing carries Data Preparation & Cleaning for ML — a structured treatment of the patterns and tooling for taking raw data through to ML-ready feature sets, covering missing-value handling, outlier detection, encoding strategies for categorical variables, scaling, and the validation patterns that catch data-quality issues before they corrupt model training.
Material is paid and aimed at engineers and analysts entering production ML work. For broader content, see CourseFlix's Machine learning category page.
