The Data Science in Economics micro-credential provides professional development in data analysis, data visualization, and presentation skills. These skills are in high demand as the volume and types of data are growing at a rapid pace. The goal is to teach students how to approach data sets methodically and identify meaningful trends, correlations, and anomalies.
At the core, students will learn critical thinking and reasoning skills necessary to assess and evaluate data as well as draw meaningful conclusions. Visualization and presentation skills enable students to communicate their findings persuasively and effectively. Students will benefit from the applied nature of the curriculum. Through the capstone empirical project, analytics practitioners will share their real life experiences with the class. Class assignments can be used as examples of acquired skills to prospective employers and academic programs. This micro-credential will be especially beneficial to students who plan to pursue career in data analytics oriented jobs.
Please see the Micro-credential website for general description of micro-credential programs and how they work.
The Data Science in Economics micro-credential is open to all UB students and no prior knowledge is required.
Please see the Undergraduate Catalog for current course descriptions.
ECO 380 and ECO 480 provide a baseline from which analytic skills are honed. ECO 461, ECO 481, or ECO 485 will reintroduce and expand the skills students learned in ECO 380 and ECO 480. The capstone project integrates analytic reasoning with visualization and communication skills. The combination enables students to test hypotheses with rigor and communicate effectively. These courses can be applied to satisfy Economics BA or BS degree requirements.
Student are required to successfully complete 3 required courses with a grade of B or better; watch five recorded lectures that are about 25 minutes long each, carry out a capstone empirical project, and make a 20 minute presentation in front of faculty members who oversee this program. The topics of these five lectures are (1) writing about data analysis, (2) how to carry out an empirical project, (3) dangers of biases and misinterpreting results, (4) data analytics and presentation in industry, and (5) how to use common statistical packages. We will assess their participation using Panopto analytics system that is based on completion rate.
For questions, please contact the Economics Undergraduate Advisor:
435 Fronczak Hall