Data mining—the art of extracting useful information from large amounts of data—is of growing importance in today’s world.
The amount of data flowing from, to, and through enterprises is enormous, and growing rapidly—more rapidly than the capabilities of organizations to use it. Enterprises are trying to make effective use of the abundance of data to which they have access: to make better predictions, better decisions, and better strategies. Therefore, managers now need to know about the possibilities and limitations of data mining.
This course introduces data mining problems and tools to enhance managerial decision making. Students will learn how to ask the right questions and how to draw inferences from data by using the appropriate data mining tools. This course will enable students to approach business problems data-analytically, envision data mining opportunities in organizations, and follow up on ideas or opportunities that present themselves.
Students will gain skills in the following areas:
Adjunct Professor of Business Analytics
George Mason UniversitySchool of Information Systems and Operations Management
Open source data science and statistical computing software available through a cloud-based application. An R environment will be set-up for students in MIS 431 and an access link will be provided through Blackboard.
Available at the following link: RStudio Cloud
RStudio Cloud Guide: https://rstudio.cloud/learn/guide
DataCamp offers interactive R and Python courses on topics in data science, statistics, and machine learning. Students can learn through short video tutorials and interactive exercises from within their web browser. Courses on DataCamp do not require any software installation to complete.
Students in MIS 431 have been granted access to all DataCamp courses for a 6-month period. DataCamp will serve as a tool for MIS 431 students to enable learning programming concepts through hands-on interactive exercises.
In MIS 431, students are required to complete three DataCamp courses during the semester (150 points towards the final grade). Each course requires approximately 4 to 6 hours to complete.
Links to the description of the courses are provided below.
Students will receive an access link to join the MIS 431 team in DataCamp through Blackboard. After clicking the link, students will first be prompted to create an account. Students must use their GMU e-mail address to enroll (email@example.com) and add their name as it appears in GMU records.
Slack is a tool for collaboration where students can interact with their peers as well as the professor throughout the course. Students will receive an access link to join the MIS 431 Slack group.
Please go through the tutorial below for a quick introduction to using Slack.
All course textbooks for MIS 431 are freely available on the web. Links are provided below.
The textbooks below are optional for this course, but I highly recommend that students read these books after completing MIS 431 to further develop their machine learning skills.
For details about this semester, please refer to the course syllabus
Copyright © David Svancer 2020