Graduate Certificate in Business Analytics

This course teaches students how to maximize spreadsheets as a data management tool using advanced functions and formulas. Students will learn how to efficiently manipulate, format, and automate data, and use spreadsheets to build customized reports, dashboards, amazing charts, pivot tables and macros. This course is applicable to all business disciplines. Prerequisites: basic spreadsheet knowledge. (3 Credits)

This course provides an introduction to Business Intelligence, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making.  Business Intelligence requires foundation knowledge in data storage and retrieval, thus this course will review logical data models for both database management systems and data warehouses. Students will learn to extract and manipulate data from these systems and assess security-related issues. Data mining, visualization, and statistical analysis along with reporting options such as management dashboards and balanced scorecards will be covered. (3 Credits)

This course provides an introduction to programming with a focus on business and analytics applications. The curriculum supports the development of skills in data extraction and manipulation as well as automating data analysis tasks. Students will become adept in the use of important libraries and will be able to use trusted open-source resources to support continued development of programming skills. No prior programming experience expected. (3 Credits)

This course provides an overview of statistical analysis and inference. The language and methods of statistics are used throughout the MBA curriculum, both in the classroom and in assigned readings. In addition, the language and methods of statistical analysis have permeated much of academic and professional writing as well as media reporting, both inside and beyond the business community. The goal is to present a broad introduction to statistical thinking, concepts, methods, and vocabulary. The course has an emphasis on business applications. (3 Credits)

This course provides an introduction to topics in managerial data mining, and related data retrieval and manipulation content. Models in regression, clustering, neural nets, classification, and association rule mining are applied to business data sets. In this managerially-focused course, students will learn how to use such models and interpret output. Students will also be introduced to a programming language for extraction and manipulation of data. Experiential exercises will be assigned using leading industry applications. (3 Credits) Prerequisite: 650 

This graduate course provides comprehensive coverage of project management, focusing on the methods and competencies needed to effectively manage projects. Upon successful completion of this course, students will be able to understand different project management techniques, terminology and trends; define project success measures and methods; improve quality, cost and efficiency with the project management process; and gain basic competency using project management software. (3 Credits)

This course covers essential concepts and methods to foster data-driven decision-making to motivate business insight and innovation. Lessons cover topics in big data, algorithmic thinking, machine learning, data visualization, and communication. Projects spanning several weeks focus on business problems that can be solved through the application of cutting-edge Data Science techniques. Students develop proficiencies in the use of Python, R, and Tableau by completing regular exercises and projects using real data. No prior programming experience is expected. (3 credits)