This course covers mathematical modeling and optimization fundamentals in the context of machine learning. Key areas include optimization basics, heuristics, data handling, interpretable machine learning models, and regression from an optimization perspective. It delves into Support Vector Machines and Large Language Models, along with the field of Natural Language Processing. Practical skills are developed through coding exercises and a hands-on project, combining theory with application.