Master's Degree in Computational and Quantitative Methods

Degree: Master of Science
Major: Computational and Quantitative Methods
Hours: 30

Delivery Options:

Computational and Quantitative Methods Degree Overview

The �鶹AV Master of Science Degree in Computational and Quantitative Methods is for anyone interested in using mathematical tools in data analysis, with applications in mathematics, statistics, finance, computer science or accounting courses. Mathematics and statistics professionals who are products of of CMQM are trained to work in several areas that involve the use of modern tools and technologies for analyzing large and high dimensional data, generating possible trends and using outcomes to make complex and informed decisions.

�鶹AV has a vibrant campus community. Our mathematics faculty are engaged in current research, and strive to engage our students in project-based learning. Students entering this program can expect direct contact with talented faculty who are interested in extending their students' knowledge. Students who graduate from the program will be well placed to work in a variety of careers in emerging fields.

Applicants need to have a cumulative GPA of 2.5 (on a four-point scale). GRE scores are optional. International applicants must have an English proficiency score.

Computational and Quantitative Methods Courses You May Take

Probability Theory/Stochastic Processes: Theory of probability, random variables, well-known distributions, conditional probability, Bayes' formula, Markov Chain, counting process, Poisson processes, Chapman-Kolmogorov equations, gambler's ruin, branching process.

Time Series Analysis: This course covers methods for analyzing data collected over time. Topics include autoregressive moving average models (MA, AR, ARMA, ARIMA), exponential smoothing, model identification, parameter estimation, diagnostics and forecasting. Appropriate statistical software (such as ITSM, R or SAS) used throughout.

Predictive Analytics: Advanced statistical techniques for analyzing large and high dimensional data. Topics include data mining strategy, data processing, predictive modeling techniques for decision making, model assessment and comparison. This course will be taught using appropriate statistical software.

Internship: This is a supervised internship course resulting in the completion of a comprehensive final report. Internship is intended to provide students with hands-on experience in industry in an area related to Computational and Quantitative Methods. Each student is assigned to an industry partner and works with this partner at least 12 hours per week for one semester on a project involving data-driven decision making.

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Tuition and Fees

Career Paths for Computational and Quantitative Methods

The study of the market reveals an increasing national and global demand for mathematics and statistics related professionals. According to the Occupational Outlook Handbook, general employment in mathematics occupations is projected to increase 29% from 2021 to 2031, significantly faster than the average for all occupations; this increase is expected to produce approximately 82,000 new jobs over the decade. The study also projects the following growth rates: 36% for data scientists, 31% for mathematicians and statisticians, 23% for operation research analyst, 21% for actuaries, and 9% for financial analyst (Bureau of Labor& Statistics, 2022).