DATA MINING PLANNING AND MANAGEMENT

LIS 501

Introduces computational methods and tools for processing, analyzing, and understanding text data. Topics include text data preparation and preprocessing, models of text content and meaning, exploratory text analytics, text classification, information extraction from texts, ethical issues in natural language processing (NLP), and related applications in information sciences and other fields. Develops practical skills to design and implement text mining solutions using popular NLP tools and programming packages.

COMARTS/LIS 705

Introduces key stages in the processes of gathering and analyzing data for decision making, including tasks, methods, and tools used at each stage. Topics include developing the research question from organizational goals, choosing appropriate data collection methods, sampling, basics of measurement and question design, managing and visualizing data, descriptive statistics and basic inferential statistics such as correlations, regressions, and ANOVA.

LIS 440

Provides an introduction into the world of Data Science. Includes hands-on projects using scenarios involving analysis of real-world data and development of graphical visualizations. Introduces statistical tests, data management, data programming, data ethics and visualization of data.

GENBUS 704

Exploration of statistical inference and data analytics tools. Review of relevant foundations of statistics, machine learning and probability theory. Emphasis on applying the resulting concepts to canonical business examples, using both Excel and R.

OTM 703

Introduction to business analytics, machine learning and artificial intelligence from a managerial perspective. Covers identifying opportunities to capture data, learning about the current trends in and possibilities with data mining, converting analytics insights into action and evaluating your organization's readiness to compete with analytics.