CT 5320 - Data Mining for Data Science and Analytics

This course introduces students to the principles and practice of analytics through statistical modeling and data management. Many business problems still utilize traditional statistical and data mining tools. This course introduces several modeling tools like multiple linear and logistic regression (MLR), Hierarchical linear model (HLM), multiple discrimination analysis, factor analysis, introduction to Bayesian statistics, and cost and objective functions. In addition, it introduces Monte-Carlo simulations and rules of probability distributions. Prerequisites: AI 5120, CT 5610, CT 6110, CT 6440, CT 6540, CT 6915 Credits: 4 Students cannot take both CT 5325 Data Mining and Statistical Modeling and CT 5320 Data Mining for Data Science and Analytics for credit.