Based on theoretical foundations and practical applications, students will be able to understand and implement machine learning approaches for drug discovery and molecular property prediction. They will learn how to represent molecular structures computationally, select relevant features, build predictive models, interpret results, and generate novel molecular structures, gaining hands-on experience with modern deep learning frameworks and cheminformatics tools.