SCO6191
SCO 6191 - Big Data Analytics in Supply Chains (2 Cr.) Online may be available
Supply Chain & Operations (11270)
TCSM - Curtis L. Carlson School of Management
SCO 6191 - Big Data Analytics in Supply Chains (2 Cr.) Online may be available
Course description
With the advancement of digital technologies and networking capabilities, firms are actively engaged in capturing “big” data related to their supply chains. Firms recognize the immense potential in mining big data for improving the quality and timeliness of decisions, and becoming proactive in sensing and responding to external and internal signals of threats and opportunities. The course develops the capability to analyze and interpret structured and unstructured data that is fundamental to managing supply. The data analytics methods covered in the course include statistical methods (e.g., multivariate regression, logistics regression, GLMM, LASSO), machine learning methods (e.g., support vector machine, ensemble methods – random forest, gradient boosting model) and optimization methods (e.g., deterministic and stochastic methods). Through a combination of operations analysis case studies and hands-on exercises, students learn (i) various facets of data analytics: data access, data aggregation, data analysis and data visualization; (ii) appropriateness and inappropriateness of big data analytic methods; and (iii) big data based predictive analytics. The final course project involves designing and testing of prototype systems in supply chain and operations settings of companies.
Minimum credits
2
Maximum credits
2
Is this course repeatable?
No
Grading basis
A-F - A-F Grade Basis
Lecture
Requirements
009472
Typically offered term(s)
Every Fall