Master of Professional Studies in Data Science

Master of Professional Studies programs in data science offer instruction in aspects of managing large-scale data, including data visualization, data mining, and data warehousing.

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Programs granting Master of Professional Studies degrees in data science focus on using data management techniques to address data-related challenges faced by businesses and industries. These degree programs include coursework in analytics, data mining and modeling, and machine learning.

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Master of Professional Studies in Data Science Program Information

These Master of Professional Studies programs cover methods of collecting, analyzing, and modeling large-scale data sets, and they often draw from multiple departments within a university, including information systems, engineering, geography, and statistics. Curricula might offer a broad course of study in data science or allow students to focus on areas like data analytics and statistical modeling. These programs usually require approximately 30 credit hours or two to three years of study, and classes including those listed below may be available in hybrid or online formats.

Introduction to Analytics

Introductory courses in these programs offer an overview of methods for data analysis in business and industry. Students examine key aspects of predictive analytics and tools for data analysis, including Excel. Students may study real-world applications of analytic techniques in sectors like government and retail. Topics of discussion also include how data analysis shapes organizational decision making.

Data Mining

These classes offer instruction in the use of data mining techniques to identify patterns within large data sets. Students are introduced to association-rule mining, Bayesian networks, decision trees, and other data mining techniques. Students may use case studies to understand how databases and data mining impact decision making within organizations. Specific data analysis software packages may also be covered.

Statistics

Due to the quantitative nature of the field, these curricula include one or more statistics classes. These courses introduce foundational aspects of probability theory and may cover regression, correlation, analysis of variance, and sampling. Students investigate hypothesis testing in general and learn specific statistical tests like chi-square tests and ANOVA. Classes may focus on more specific applications of statistics to areas like spatial phenomena. Software packages for statistical analysis may be implemented.

Data Visualization

Students in data visualization classes learn about general approaches to and methods for visualizing large data sets. Courses may focus on techniques for visualizing multidimensional data and include a discussion of topics like dynamic data updates and temporal modeling. They may also incorporate communication theories applicable for conveying data-related messages to various audiences. Courses in data visualization are often project based, incorporating labs and instruction in tools and software including HTML5, JavaScript, and R Shiny.

Data Warehousing

These programs may include courses on storage techniques applicable to large data sets. Data warehousing classes cover how organizations design and construct data warehouses and how approaches to warehousing impact data mining. Students may learn about SQL and data modeling along with column-based and NoSQL database systems.

Master of Professional Studies in Data Sciences Program Admission Information

Applicants to these Master of Professional Studies programs must have earned a bachelor's degree, and some programs require a minimum GPA of 3.0 during at least a portion of undergraduate study. No particular major is mandated, but programs often prefer applicants with a degree in science, engineering or a related quantitative discipline. Regardless of their major, applicants should have completed statistics and calculus classes and have some programming experience. Some programs require GRE or GMAT scores and letters of recommendation. Applicants may also need to submit a statement of goals and a resume.

Master of Professional Studies degree programs in data science prepare students to handle challenges associated with managing large-scale data in a variety of industries. Students with the appropriate background for these programs can expect coursework in data warehousing and mining along with an emphasis on quantitative methods and statistics.

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