Data Mining for Business Intelligence
This course will cover advanced micro-level data analytics, advanced data mining techniques to discover knowledge and acquire business intelligence from massive datasets, pattern recognition, including fraud detection, consumer behavior, credit approval etc. The course will also cover the most important data mining techniques—classification, clustering, association rule mining, visualization, prediction—through a hands-on approach using XL Miner and other specialized software, such as the open-source WEKA software.
- Vercellis, C. (2009). Business intelligence: data mining and optimization for decision making. New York: Wiley.
- Shmueli, G., Bruce, P. C., Yahav, I., Patel, N. R., & Lichtendahl Jr, K. C. (2017). Data mining for business analytics: concepts, techniques, and applications in R. John Wiley & Sons.
- WEKA Tutorial (https://wekatutorial.com/)