Course Outline

MMIS 523 : Data Mining, Machine Learning and Knowledge Discovery

Preview Workflow

Viewing: MMIS 523-WW : Data Mining, Machine Learning and Knowledge Discovery

Last approved: Wed, 20 Jan 2016 14:10:45 GMT

Last edit: Wed, 20 Jan 2016 14:10:44 GMT

College of Business (WBUAD)
Data Mining, Machine Learning and Knowledge Discovery
Many organizations are familiar with "drilling down" in their data systems to see the details behind a higher-level, more abstract piece of business knowledge -- such as going from "customer complaints have risen 20% this year" to the statistical process control systems? measurements that should have warned us of that before disaster struck! Data mining is both finding the right data in one?s file systems or data warehouses, by applying smarter search and filtering criteria, as much as it is the reduction, analysis and presentation of that data in meaningful ways. While many of these techniques are statistical in nature, many rely on applied artificial intelligence algorithms -- so-called "machine learning" -- to help the organization's managers, accountants and lawyers in "discovering" new knowledge in the sea of data that they already have, but cannot digest without significant software help. But data mining and knowledge discovery is not just the domain of "Big Data", as books such as Big Data for the Little Guy, and small business analytics web pages at major big data providers demonstrate. This course surveys these methodologies, and guides the student in identifying the criteria to use to define, manage and operate a successful data mining and machine learning system that meets organizational needs. Prerequisites: MMIS 501 and MMIS 502, or approval of the Program Chair

The student will develop an understanding of how data is described and prepared for analysis, and will be familiar with various machine learning methods for visualizing data. Additionally the student will understand the methods of data mining and knowledge discovery from a management perspective.

Upon completion of this course, students will be able to: Lead and manage knowledge discovery efforts. Understand strategic aspects of knowledge discovery. Respond to the regulations associated with data mining and use of discovered knowledge. Use knowledge discovery in quality management efforts. Understand the cultural impacts of data mining and knowledge discovery. Formulate changes to the data collected in response to corporate goals and within cultural and governmental constraints.

Located on the Daytona Beach Campus, the Jack R. Hunt Library is the primary library for all students of the Worldwide Campus. The Chief Academic Officer strongly recommends that every faculty member, where appropriate, require all students in his or her classes to access the Hunt Library or a comparable college-level local library for research. The results of this research can be used for class projects such as research papers, group discussion, or individual presentations. Students should feel comfortable with using the resources of the library. 

Web & Chat:
Text: (386) 968-8843
Library Phone:  (386) 226-7656 or (800) 678-9428


Written assignments must be formatted in accordance with the current edition of the Publication Manual of the American Psychological Association (APA) unless otherwise instructed in individual assignments.

ActivityPercent of Grade
Input Grading Item100

Undergraduate Grade Scale

90 - 100% A
80 - 89% B
70 - 79% C
60 - 69% D
0 - 60% F

Graduate Grade Scale

90 - 100% A
80 - 89% B
70 - 79% C
0 - 69% F
Steve Chadwick - 2/23/2015
Lela Halawi - 2/23/2015
Aaron Glassman - 2/23/2015
Bobby McMasters
1-5 Master of Science in Management Information Systems Understand the role of information and knowledge in organizations, and how to apply information management and knowledge management principles and techniques to support the accomplishment of organizational goals and objectives.
2. Use the principles of quality management to implement continuous business process improvements that achieve information systems’ reliability and robustness in sustainable ways.
3. Understand and apply systems engineering principles to the requirements analysis, design, development, implementation and operational support of organizational information and knowledge management systems.
4. Integrate various ethical, legal, technological and professional perspectives, both local and global, throughout the various MIS decision making and managerial and leadership processes.
5. Lead and manage the various aspects of information and knowledge management, stewardship and governance within a variety of organizational and mission contexts.

Key: 354