The University of Colorado Boulder’s Professional Master’s Degree in Applied Mathematics is designed to give students the technical knowledge and professional
skills to be highly successful in careers related to data science, statistics, applied mathematics and engineering. Coursework -- culminating in a comprehensive final project -- offers students strong preparation in mathematics, statistics, and computing at the heart of the big data revolution. In addition, students will have access to workshops and courses that help develop valuable professional skills, including communication, collaboration, presentation, and networking skills. As a part of our program, students engage in a hands-on, experiential education, with opportunities for networking with campus faculty and off-campus professionals. Our internationally recognized faculty have both academic and industrial experience. Many are fellows of professional societies, including the Society for Industrial and Applied Mathematics (SIAM), the American Mathematical Society, the American Statistical Association, and the American Physical Society. The department is also home to active student chapters of the Association of Women in Mathematics (AWM) and the Society for Industrial and Applied Mathematics.
Students in the program will have the option to specialize in Statistics and Data Science or customize their own educational plan. The Statistics and Data Science specialization enables students to develop the foundational tools needed to analyze and interpret data, including complex and high dimensional datasets. In addition, students will have the opportunity to participate in the department’s Laboratory for Interdisciplinary Statistical Analysis (LISA). Here, students will gain valuable collaboration skills and foster relationships with faculty and industry professionals. Students not wishing to specialize in Statistics and Data Science can forge their own path with a customized educational track that capitalizes on the Applied Mathematics Department’s numerous strengths including computational mathematics, statistics and data science, physical applied mathematics, mathematical biological and social sciences, and mathematical geosciences.