The course outline is available HERE.
This course equips students with basic analytical tools that support business decision making. Students learn the principles of statistics and other techniques and apply them to data analysis using computer-based tools. In addition, students develop a broader understanding of the information systems that supply these data, and how quantitative analyses support management and strategy in business organizations. 1 Credit.
With Big Data and Analytics becoming mainstream in public and private sectors, decision support systems have become even more important elements in effective decision-making. Managers increasingly rely on data and synthesized information to make decisions. This course exposes graduate students to the fundamentals of decision support systems. This course will focus on data mining techniques used in managerial decision-making. The course will use state-of-the-art computing software, R, and data-mining extensions written for R, such as R Commander and rattle. R and its extensions, despite being the state-of-the-art, are freeware and hence allow students to learn the most advanced analytic methods and to graduate with skills they can readily apply in their new roles as analysts and managers.
The specific objectives of this course as follows:1. Introduce students to decision support systems
2. Introduce students to data mining techniques
3. Expose students to advanced data mining methods in a hands-on environment, such as regression and classification methods
4. Review applications of data mining methods in businesses