CS 45700 - Introduction To Data Mining

Data mining refers to the process of automatic discovery of patterns and knowledge from large data sets. As an introductory course on data mining, this course presents the knowledge discovery process, and introduces data preprocessing and exploration, major data mining tasks, the relevant methodologies and techniques, and data mining applications from different disciplines.

Preparation for Course
P: CS 36400 or IST 27000, and STAT 51100 or 30100, or consent of instructor.

Cr. 3.
Notes
Junior or senior class standing required.
Student Learning Outcomes
We expect the proposed course aspires higher order learning outcomes in critical thinking, analysis, research and communication.
1. Understanding the Knowledge Discovery in Databases (KDD) process (a, c)
2. Understanding data characteristics, and data exploration and data preprocessing methods(b, i)
3. Understanding principles of multidimensional data analysis (b, c, i)
4. Understanding principles and methods of frequent pattern mining (b, c, i, j)
5. Understanding principles and methods of cluster analysis (b, c, i, j)
6. Understanding principles and methods of data classification (b, c, i, j)

The letters in parenthesis refer to ABET Program Learning Outcomes for Computer Science:
(a) An ability to apply knowledge of computing and mathematics appropriate to the discipline
(b) An ability to analyze a problem, and identify and define the computing requirements appropriate to its solution
(c) An ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs
(d) An ability to function effectively on teams to accomplish a common goal
(e) An understanding of professional, ethical, legal, security and social issues and responsibilities
(f) An ability to communicate effectively with a range of audiences
(g) An ability to analyze the local and global impact of computing on individuals, organizations, and society
(h) Recognition of the need for and an ability to engage in continuing professional development
(i) An ability to use current techniques, skills, and tools necessary for computing practice.
(j) An ability to apply mathematical foundations, algorithmic principles, and computer science theory in the modeling and design of computer-based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices.
(k) An ability to apply design and development principles in the construction of software systems.