Analytics and Modeling (or computational science) is the field of study that focuses on the integration of knowledge and methodologies from mathematics, statistics, and computer science to analyze and solve problems in science, engineering, and other fields. From mathematics come mathematical modeling (both continuous and discrete) and numerical analysis; from statistics come methods for processing and analyzing large quantities of data; from computer science come simulation and modeling, the design and analysis of algorithms, and combinatorial optimization. As scientific and engineering fields deal with increasingly complex and expanded information and datasets, the need for individuals with such computational skills is expected to expand greatly.
The 36-credit program in Analytics and Modeling is particularly designed for students with interest and preparation in science, engineering, mathematics, and/or computer science. The program prepares such students for a future in which computation will play an ever-increasing role in solving science and engineering problems and in creating new scientific knowledge. Specifically, the program is designed as a professional master’s degree that provides students with a set of highly marketable skills applicable to many areas of science, industry, business, and government.
Although the program is designed for individuals having a wide range of academic and work backgrounds, appropriate preparation for the program involves an understanding of science, typically demonstrated by at least an academic minor in a traditional science field, as well as some basic mathematics, statistics, and computer science coursework (see Admission requirements). Given the appropriate preparatory coursework, the program can be completed in 1.5 years.
Students enrolled in this program will:
Admission. Applicants must meet the general admission requirements of the Graduate School, including having a minimum GPA of 3.0 and submitting letters of recommendation, transcripts, and a personal essay. In addition, applicants should have the equivalent of a minor in a science or engineering field as well as basic coursework in mathematics (e.g., calculus and linear algebra), statistics, and computer science (e.g., a course in programming and one in simulation and modeling). Students not meeting the general admission requirements or lacking preparation may be admitted provisionally assuming they complete the preparatory coursework either at Valparaiso University or another institution prior to full admission to the program. For international students, a minimum TOEFL score of 80 or IELTS of 6.0 is required.
Curriculum. Students complete four required core courses built around statistics, databases, and visual imaging, and take at least two courses (6 cr) in computational applications in science, engineering, or other applied areas. Students also complete either an internship experience or a research project. To allow specialization, students fill out the program with elective coursework in computational science applications, mathematics, or computer science.
|Core Requirements (12 credits)|
|MATH 540||Statistics for Decision Making
|IT 633||Data Mining
||Simulation and Modeling
|Core Applications in Computational Science (6 credits)|
|Choose minimum of two:||
|MATH 521||Mathematical Models of Infectious Disease||3 cr|
|CTS 560||Computational Molecular Science||3 cr|
|CTS 640||Topics in
|CTS 650||Computational Social Science
|Experiential Training (3 credits)|
|Electives (15 credits may be selected from Core Applications or from below)|
|CS 565||Interactive Computer Graphics||3 cr|
|CS 572||Computability and Complexity||4 cr|
|CTS 545||Evolutionary Algorithms||3 cr|
|CTS 550||Scientific Visualization||3 cr|
|CTS 590||Topics in Computational Science||3 cr|
|CTS 690||Advanced Topics Computational Science||3 cr|
|GEO 515||Advanced Geographic Information Systems||3 cr|
|IT 664||Natural Language Technologies||3 cr|
|MATH 520||Dynamical Systems
|MATH 523||Game Theory||3 cr|
|MATH 530||Partial Differential Equations||3 cr|
|MATH 543||Time Series Analysis
|MATH 544||Applied Probability and
Statistical Decision Theory
|MATH 570||Numerical Analysis
|MATH 571||Experimental Mathematics||3 cr|
|MATH 530||Numerical Weather Prediction
Special 4+1 BS/MS Program Option for undergraduate students at Valparaiso University
Undergraduate students at Valparaiso University may complete the MS in Computational Science in one year by following a special track that ensures completion of all admission requirements and allows elective graduate computational science coursework during their senior year. As part of their undergraduate study, such students will have either:
1. earned a mathematics or computer science major along with a science minor, or,
2. earned a minimum major in one of the natural sciences or engineering fields (e.g., Astronomy, Biology, Biochemistry, Chemistry, Environmental Science, Meteorology, Physics or any field of Engineering) and completed the follow mathematics and computer science courses with a B or higher:
Students are also encouraged to take MATH 132 Calculus II and CS 158 (Algorithms and Abstract Data Types).
Students meeting the above requirements with a 3.2 overall GPA and a 3.0 science or engineering GPA will be guaranteed admission to the 4+1 BS/MS program. Others may be considered on an individual basis. Students interested in pursuing this track should consult with the Graduate Office and/or the Computational Science Program Director during their junior year or, at the latest, in the fall of their senior year.
Valparaiso University students pursuing the BS/MS track that have completed MATH 340 or CS 325 during their undergraduate study rather than MATH 540 or CS 525 may have these core requirements waived if the course instructor or their academic adviser confirms that graduate level requirements for the courses have been successfully completed.
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