Data Analytics Certificate
Program Availability: OnlineProgram Length: 15 Hours
Program Overview
A&M–Central Texas’ accredited 15‐hour online undergraduate Data Analytics Certificate builds in‐demand, fundamental skills for developing professionals in data analytics. Whether you want to increase your skill set for your current job or look to re-skill for new career opportunities, the undergraduate Data Analytics Certificate delivers expertise and real-world training. Even better: If you decide to pursue a full business degree, all of your coursework will apply toward a bachelor’s degree.
If you already have a bachelor’s degree, learn more about the A&M–Central Texas graduate Applied Data Analytics Certificate.
Program Benefits and Learning Outcomes
The 15‐hour undergraduate certificate drives into the heart of modern business analytics with real-world tools and practices, including:
- Descriptive statistics, data visualization, descriptive data mining, linear regression, forecasting, optimization models, spreadsheet models, Monte Carlo simulation, and decision analysis
- Up-to-date practices for using web analytics to collect and analyze users’ “digital footprints” to improving online marketing, strengthen customer relationships and make data-driven strategic planning and decision making
- Concepts, methods, and techniques in data mining, and analyzing data mining problems and their solutions
- Understanding relational database schema, formulating queries and sub-queries of varying complexity, embedding query statements in a host language, and defining and querying data views
Accreditation
The College of Business Administration is accredited by the Association to Advance Collegiate Schools of Business (AACSB). Schools that have earned AACSB business accreditation demonstrate an ongoing commitment to excellence in teaching, research, curriculum development, and learner success.
Certificate Program Core Faculty
Department: Computer Information Systems
Associate Professor of Computer Information Systems
Email: [email protected]
Phone: 254.519.5437
Department: Computer Information Systems
Associate Professor of Computer Information Systems
Email: [email protected]
Phone: 254.519.5437
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