Graduate students interested in studying predictive analysis should pursue a Master of Science in Predictive Analytics. These degree programs are available online and in hybrid formats, in addition to traditional on-campus formats. Explore this degree program and common requirements here.
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Information for Online Master's Degree Programs in Predictive Analytics
Master's degree programs in predictive analytics generally culminate in a thesis or capstone project and may offer different concentration areas, such as computational methods, healthcare, marketing or hospitality. Electives for these programs may vary, especially for different concentrations, but some common course topics are discussed below.
Regression and Analysis
Students typically take a course in regression that is paired with general data analysis or specific analysis, such as multivariate analysis. These courses typically include hands-on experience with statistical software as students work with practice problems. Specific course topics may include robustness, multiple regression and correlation, analysis of variance and more.
These degree programs usually include an introductory course in statistical analysis that offers students a broad survey of statistics that will be built upon as the program progresses. Students examine various data analysis methods, descriptive statistics and sampling techniques. These courses may address topics in hypothesis testing, estimation, data visualization, simple linear regression and more.
Time Series and Forecasting
Students in these courses study the different time series analysis and forecasting models and the application of these models to predictive analysis. These courses allow students to experiment with real-world problems and examples in financial data and how they apply to risk management and other subjects. Specific topics may include Box-Jenkins models, diagnostics checking, volatility models, forecasting evaluation and more.
Courses in data visualization focus on the analysis techniques for large data sets. Students may explore data sets from various fields, such as business, science and engineering, and experiment with different kinds of visualization software. These courses discuss topics in isosurface generation, effective visualization design, visual encoding, basic network visualization and volumetric rendering techniques.
Degree programs in predictive analytics usually offer a course that explores machine learning. These courses typically discuss the practical applications of data mining and machine learning techniques that may be applied to subjects like social media analytics, searching and ranking and more. Students learn about programming language and get hands-on experience with machine learning algorithms.
Common Entrance Requirements
Students applying to master's degree programs in predictive analytics typically need to hold a bachelor's degree. Some of these programs may have a minimum GPA requirement and/or require applicants to have prior coursework in calculus. Depending on the program, admissions committees may also like to see any related professional experience in the field. Applicants to these programs usually need to include their official transcripts, letters of recommendation, a statement of purpose and/or a resume or CV with their application.
Master of Science in Predictive Analytics degree programs are available fully or partially online and cover a wide range of computational and analytical topics. These degree programs generally conclude with a final project, thesis or internship opportunity.