Course Number: 95-791
Data mining is the science of discovering structure and making predictions in large, complex data sets. Nowadays, almost every organization collects data, which they hope to use to support improved decision making. Learning from data can enable us to better: detect fraud, make accurate medical diagnoses, monitor the reliability of a system, perform market segmentation, improve the success of marketing campaigns, and much, much more.
This course serves as an introduction to Data Mining for students in Business and Data Analytics. Students will learn about many commonly used methods for predictive and descriptive analytics tasks. They will also learn to assess the methods' predictive and practical utility.
• Use R to run many of the commonly used data mining methods
• Understand the advantages and disadvantages of various methods
• Compare the utility of different methods
• Reliably perform model/feature selection
• Use resampling-based approaches to assess model performance and reliability
• Perform analyses of real world data
95-796 Statistics for IT Managers 6 Credits