The Undergraduate Data Analytics Certificate (DAC) is a collaborative, cross-disciplinary program. The certificate is designed for students who aspire to work in academic, governmental, non-profit, and commercial sectors as data scientists. The demand for data scientists has grown significantly as both private and public organizations generate and collect increasingly larger amounts of data; but the need to collect, analyze, and interpret such data requires a broad set of analytical skills. Through the Data Analytics Certificate, students will receive training in data management, quantitative analysis, and visualization techniques that will allow them to properly collect, contextualize, and communicate findings based on quantitative data.
Program of Study
The certificate requires 12 credit hours (4 courses). No more than three courses per discipline will count toward the certificate. Course substitutions or exceptions can be made with the approval of the certificate faculty adviser within each respective college.
Courses in the program will usually be offered as part of existing majors. Also, departments may occasionally offer the courses online (fully or hybrid), and in the summer (but not in the Maymester). The Data Analytics will be an embedded certificate.
- Demonstrate proficiency in data collection, management, analysis, and visualization.
- Demonstrate proficiency in quantitative analysis techniques for effective data-driven decision-making.
- Demonstrate proficiency in various data management and analysis software programs such as: R, SAS, SPSS, and STATA.
- Applicants to the Data Analytics Certificate must meet the requirements for their major.
- Students may pursue this certificate in conjunction with their major program.
- Students can apply to enroll in the DAC program in the Department of Political Science Department or the Department of Economics.
- To fulfill the certificate requirements students must successfully complete 12 credit hours from the courses listed below, and make a public presentation of a data driven research project. Presentations can take place at UWG (Research and Big Night), at student or professional conferences (NCUR), etc. It is highly recommended that students complete courses from areas 1 and 2 first, and then select courses from areas 3 and 4 below.