This program 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 simulations and modeling, the design and analysis of algorithms, and combinatorial optimization. As scientific, engineering, and business 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 business, 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 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 intended for individuals having a wide range of academic and work backgrounds, appropriate preparation for the program involves an understanding of business or science, typically demonstrated by at least an academic minor in a traditional business or 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:
- Learn a high-level programming language
- Acquire knowledge of applied mathematics
- Demonstrate knowledge of computational methods
- Learn and apply simulation and modeling skills
- Be able to apply computational modeling techniques to one or more STEM (science, technology, engineering, mathematics) disciplines or business
- Learn to communicate the solution process effectively
Admission
Applicants must meet the general graduate admission requirements (see here ). In addition, applicants should both:
- Have the equivalent of a major or minor in a business, engineering, science, mathematics, or statistics field
- Have basic coursework in mathematics (e.g., calculus and linear algebra), statistics, and computer science (e.g., a course in programming).
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.
Students may be eligible for admission to this program as an Early Entry student. To be eligible for Early Entry, a student must have completed the basic mathematics, statistics, and computer science coursework normally required. This is usually fulfilled by taking STAT 140 or STAT 240, CS 157, MATH 131, and MATH 260 or MATH 264. See here for more information.
Curriculum
Students complete five required core courses built around statistics, databases, and simulation, and take at least one course (3 Cr.) in computational applications in science, engineering, business, or other applied areas. To allow specialization, students fill out the program with elective coursework in business, computer science, economics, information sciences, natural sciences, mathematics, or statistics.
Capstone Requirement
The Analytics and Modeling program requires a capstone experience. To fulfill this requirement, three options exist:
- AMOD 686 : The Internship option, which expects 300 hours of practical experience in a working computing environment that embraces and extends the student’s coursework and experiences.
- AMOD 792 : The Research Project, which provides the student with the opportunity to investigate or test an idea or area within the scope of data science, but on a smaller scale than that done in the thesis option.
- AMOD 798 and AMOD 799 : The Thesis. This requires two semesters of work, and is the most rigorous of the three options, requiring a proposal/plan (AMOD 798 ) and a semester of writing/execution (AMOD 799 ). This entails a minimum of two supervising faculty as the thesis committee; one of whom must be hold a tenured or tenure-track appointment. One of the participating faculty functions as the technical advisor and primary supervisor. The option adds 3 credits to the overall number of credits taken to complete the degree, as the pair of courses requires 6 credits. The resulting work is submitted to the Graduate Office. Thesis completion requires adherence to the guidelines outlined in the Thesis Manual, available on the Graduate Office academic forms website.
GRD 683 must be taken prior to the start of the any of the capstone experience options; this requirement can be waived on the recommendation of the Program Director and approval from the Dean of the College of Arts & Sciences.
Additional graduate courses may be approved by the advisor, typically from the areas of business, computer science, economics, information sciences, mathematics, natural sciences, and statistics.
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