Cheng Wang, PhD
Liberal Arts 394G
- Data Science BS, BS/MS
- Data Science Graduate Certificate
- Data Science MS
- Engineering and Applied Science PhD
- Mathematics BA, BS
A graduate-level course on mathematical methods in science and engineering. Topics include: scalar and vector field theory, linear algebra, partial differential equations and integral transforms.
Research investigations of a fundamental and/or applied nature defining a topic area and preliminary results for the dissertation proposal undertaken before the student has qualified for EAS 701. With approval of the student's graduate committee, up to 15 credits of EAS 601 may be applied to the 30 credit requirement for dissertation research.
A calculus-based introduction to statistics. This course covers probability and combinatorial problems, discrete and continuous random variables and various distributions including the binomial, Poisson, hypergeometric normal, gamma and chi-square. Moment generating functions, transformation and sampling distributions are studied.
A special course to meet the needs of students for material not encountered in other courses. Topics dealt with require the approval of the departmental chairperson.
- Numerical analysis
- Numerical PDEs