Topics in Mathematics of Data Science
MIT OpenCourseWare offers this research-oriented course on the theoretical foundations of algorithms that extract information from data, sitting at the intersection of mathematics, applied mathematics, computer science, electrical engineering, statistics, and operations research. Aimed primarily at undergraduates with research interests but welcoming to graduate students, the course is mostly self-contained and builds toward open problems in the field rather than settled textbook material. Materials include lecture notes covering topics such as high-dimensional geometry, spectral methods, and statistical estimation as they relate to data analysis. As with other MIT OpenCourseWare offerings, all content is free to access online, with no registration or fee required, though no certificate is issued. The course suits students who already have a solid footing in linear algebra and probability and want exposure to current research questions in the mathematics underlying data science.