Knowledge Discovery and Data Mining

General information

• Course Title: Knowledge Discovery and Data Mining

• Course Code: CS 513

• Academic Level: Graduate

• Instructor: Khasha Dehnad

• Department: Computer Science

• University: Stevens Institute of Technology

• Course Period: Spring Semester in 2023 (Jan 2023 - May 2023)

Course description

This course introduces fundamental and practical tools, techniques, and algorithms for Knowledge Discovery and Data Mining (KD&DM). It provides a balanced approach between methods and practice. On the methodological side, it covers several techniques for transforming corporate data into business intelligence. These include: Probability, Exploratory Data Analysis (EDA), K-Nearest Neighbors (KNN), Naive Bayes (NB), Decision Tree, Randon Forest, Artificial Neural Network (ANN), and Hierarchical Clustering. To illustrate the practical significance of the various techniques, half of the course is devoted to case studies. The case studies, drawn from real-world applications, demonstrate application of techniques to real-world problems.

Skills

• Programming: R
• Software: R Studio
• KDDM Skills: Probability, Exploratory Data Analysis (EDA), K-Nearest Neighbors (KNN), Naive Bayes (NB), Decision Tree, Randon Forest, Artificial Neural Network (ANN), Hierarchical Clustering