Curriculum Design for Students in Mathematics: Data Science Courses as Examples

The STEM (Science, Technology, Engineering, and Mathematics) academic discipline has attracted a lot of attention in recent years. Many universities begin to embrace the trends and propose several innovations and refinements in education, including teaching improvement, integrated curriculum, multidisciplinary programs, and capstone courses to better incubate students for future. In this paper, the experience of curriculum design and implementation for data science courses to the undergraduate program in mathematics is introduced. Based on the original focus on mathematical and computation theories, the employment of data science courses can provide students with the comprehensive theoretical and practical knowledge and skills for the challenges and industrial requirements nowadays. In addition, the curriculum is designed and implemented from the perspectives of students who major in applied mathematics (non-CS students) to better stimulate the learning, participation, exercise, and innovation. Major findings and lessons learned from the refined courses are discussed for more insight into the following deployment and refinement of the curriculum.