Data-driven decision making is critical in the current economic and business climate across industries. It is especially important and needed given the immense amounts of data-centric work in the Washington, D.C. region, which, with its unique intersection of federal government agencies, Fortune 500 businesses, and other highly advanced and tech-savvy companies, is a true epicenter of data analytics. This graduate certificate prepares students to succeed in the era of “Big Data” by equipping them with the advanced analytical techniques needed to extract meaningful insights from large data sets.
Weeknight and Saturday Options
Students taking the Graduate Certificate in Business Analytics Program have the option of enrolling in one of two sections: Weeknight class sessions on GW’s Foggy Bottom Campus or Evening and Saturday sessions at our Virginia Science and Technology Campus (VSTC) in Ashburn, Va. Please note, each section has it's own course offerings and schedule. Students interested in saturday courses at the VSTC should click here.
Completion of 12 credits of the coursework listed below to be eligible for completion
Achievement of at least a 3.0 cumulative grade point average at the time of completion
Complete all requirements within five (5) years
In addition, students should be aware of the following course application limitations:
Students may only apply a course towards two program requirements (ie MBAD 6224 may only be applied towards the MBA and one graduate certificate – the course cannot be applied towards the requirements of any other degree or certificate program beyond the two programs)
Students who opt to complete two graduate certificates may only double count up to six credits between the two. All remaining requirements (typically 18 credits for two certificates) must be unique to each certificate.
Successful applicants to GWSB’s MSBA program will have exposure and experience* in the following areas:
Applicants should have taken and obtained a B or higher in an undergraduate or graduate statistics within the last 5 years, be able to demonstrate regular use of statistics in a current or past professional position, or be able to demonstrate an adequate understanding of statistics in another way.
Higher Level Mathematics (Calculus and Linear Algebra)
In general, students should be able to demonstrate regular use of mathematics principles and methods and an adequate understanding of calculus and basic linear algebra. Applicants should have taken and obtained a B or higher in undergraduate or graduate level Calculus classes, including Calculus I (MATH1231) and Calculus II (equivalent to MATH1232). In addition, students are expected to have had some academic exposure to topics in Linear Algebra and Finite Math (equivalent to MATH1051).
Applicants should be able to demonstrate adequate exposure to and understanding of basic computer programming and software principles. Applicants need not have a specific understanding of analytics-based computer programs and software. Instead, the goal is for applicants to demonstrate that they are capable of learning the specific programs emphasized in the MSBA program.
*Applicants may satisfy the above prerequisites through an online offering such as Coursera.
Required Courses • 9 Credits
Statistics • 3 Credits
MBAD 6224 | Decision Making and Data Analysis (3 cr.)* OR
DNSC 6202 | Mathematics and Statistics for Management (3 cr.)* OR
DNSC 6203 | Statistics for Analytics (1.5 cr.) AND
Students may choose to complete either MBAD 6224, DNSC 6202, or the combination of DNSC 6203 and DNSC 6206. Students who opt to complete MBAD 6224 or DNSC 6202 must attain a grade of B+ or better. Students who do not attain a B+ or better will be required to complete DNSC 6203 and DNSC 6206.
Additional Required Courses • 6 Credits
DNSC 6211 | Programming for Analytics
DNSC 6279 | Data Mining
Electives • 3 Credits
DNSC 6209 | Forecasting for Analytics
DNSC 6214 | Pricing and Revenue Management
DNSC 6215 | Social Network Analytics
DNSC 6225 | Business Process Simulation
DNSC 6251 | Optimization Models for Decision Making
DNSC 6252 | Risk Analysis for Decision Making
DNSC 6403 | Visualization for Analytics
DNSC 6404 | Sports Analytics
DNSC 6290 | Special Topics: Big Data
DNSC 6290 | Special Topics: Digital Analytics
DNSC 6290 | Special Topics: Supply Chain Analytics