Data Mining Foundations and Practice Specialization

Data Mining is for domain experts and data scientists who are looking to understand the core concepts and techniques used to find patterns in large-scale data sets. This specialization consists of three courses: (1) Data Mining Pipeline, which introduces the key steps of data understanding, data preprocessing, data warehouse, data modeling and interpretation/evaluation; (2) Data Mining Methods, which covers core techniques for frequent pattern analysis, classification, clustering, and outlier detection; and (3) Data Mining Project, which offers guidance and hands-on experience of designing and implementing a real-world data mining project. Data Mining is an option for academic credit in the Master of Science degree in Data Science (MSDS) at CU Boulder. This course can be found on Coursera. The MS-DS degree is an interdisciplinary program that brings together faculty members from CU Boulder's departments in Applied Mathematics, Computer Science and Information Science. The MS-DS is open to individuals who have a wide range of education and/or work experience in information science, computer science, statistics, and mathematics.