Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive tutorial on implementing a basic machine learning workflow for predicting materials properties, specifically focusing on bandgap prediction from material compositions. Learn core concepts of machine learning, including data cleaning, feature generation and engineering, model assessment, training, hyperparameter optimization, and making predictions. Follow along with a practical demonstration using the Machine Learning Lab tool, addressing common challenges in materials data and their solutions. Gain insights into decision tree structures, inputs, and outputs, as well as key distinctions in machine learning approaches. Perfect for materials science and engineering students and professionals looking to apply machine learning techniques to materials property prediction.