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The big data analytics major is designed for students wishing to pursue one of the many jobs that require solving important large-scale problems in applied science, engineering, business, industry and government as well as pursue graduate work in big data analytics.
The big data analytics major is designed for students wishing to pursue one of the many jobs that require solving important large-scale problems in applied science, engineering, business, industry and government as well as pursue graduate work in big data analytics.
A minor in Computer Science is required, so that the student will develop strong programming skills for data analysis
The combination of Applied Mathematics and Statistics develops the ability to analyze data and generate predictive modelin
A senior project is required
Big Data Analytics
Big Data Analytics
Undergraduate
Check out these ideas from ODU Career Development Services and the Occupational Information Network (O*NET). A median salary is the midpoint of what people typically earn—half of those surveyed earned above the median salary, and half earned below.
MEDIAN SALARY
Analyze and manage risk management issues by identifying, measuring, and making decisions on operational or enterprise risks for an organization.
MEDIAN SALARY
Research market conditions in local, regional, or national areas, or gather information to determine potential sales of a product or service, or create a marketing campaign. May gather information on competitors, prices, sales, and methods of marketing and distribution.
MEDIAN SALARY
Conduct research in fundamental mathematics or in application of mathematical techniques to science, management, and other fields. Solve problems in various fields using mathematical methods.
Use of SAS and R to handle data sets. Topics for SAS include data input, creating permanent data sets, merging data sets, creating new variables, sorting, printing, charting, formatting, IML programming, macro programming, and an overview of proc SQL and other statistical procedures. Topics for R include data structure, control structure, writing functions, and graphics. Prerequisites: grade of C or better in STAT 130M or equivalent and a grade of C or better in MATH 316 or equivalent or permission of instructor.
An introductory course on machine learning. Machine Learning is the science of discovering pattern and structure and making predictions in data sets. It lies at the interface of mathematics, statistics and computer science. The course gives an elementary summary of modern machine learning tools. Topics include regression, decision trees, artificial neural networks, genetic algorithms, clustering, dimension-reduction, learning sets of rules, support vector machines, hidden Markov models, and Bayesian learning. The course will also discuss applications of machine learning that include data mining, bioinformatics, speech recognition, and text and web data processing. Students enrolled are expected to have some ability to write computer programs, some knowledge of probability, statistics and linear algebra. Prerequisites: MATH 312, MATH 316, and STAT 330 or STAT 331.
This course introduces students to practical applications of big data analytics. Lecture topics include an overview of the various topics in business, engineering, and government currently using big data analytics. Students will choose a project involving a real world application to explore techniques learned during other course work. Course involves written and oral presentations for students to improve communication and teamwork skills. Prerequisites: A grade of C or better in STAT 331 and STAT 405. Pre- or corequisite: BDA 431.
Students entering the Bachelor of Science program in Mathematics, Big Data Analytics should meet the minimum university admission requirements (Undergraduate Admission)
Math Core courses: 34 credits (GPA of 2.3)
Big Data specific courses: 24 credits
Minor in Computer Science
Estimated rates for the 2021-22 academic year. Rates are subject to change. Anyone that is not a current Virginia resident will be charged non-resident rates. That includes international students.
$ 360
$ 1,032
$ 250
$ 407
Here are a few ways for you to save on the cost of attending ODU. For more information visit University Student Financial aid
Our enrollment coordinators are ready to help you through the admissions process.
Robert Strozak
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1004 Rollins Hall, Norfolk, VA 23529
757-683-3685
757-683-3255
admissions@odu.edu
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757-683-3651
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