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Data Mining Foundations and Practice

The Data Mining specialization is intended for data science professionals and domain experts who want to learn the fundamental concepts and core techniques for discovering 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 can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Specialization logo image courtesy of Diego Gonzaga, available here on Unsplash: https://unsplash.com/photos/QG93DR4I0NE

Status: Data Modeling
Status: Exploratory Data Analysis
IntermediateSpecialization

Top reviews across Data Mining Foundations and Practice

JG

Reviewed Oct 1, 2023

This course was recently updated. I feel it's much better than the prior version. The videos are easier to follow, and the assignments are cleaned up as well.

YW

Reviewed Apr 23, 2026

Assignments are well designed guiding students to learn not only the concepts of data mining methods but also the necessary Python coding techniques.

Learner reviews across Data Mining Foundations and Practice

Showing: 20 of 31

Cyrus
Course: Data Mining Pipeline
1.0
Reviewed May 14, 2023Course: Data Mining Pipeline
Justin
Course: Data Mining Pipeline
5.0
Reviewed Oct 2, 2023Course: Data Mining Pipeline
Lucas
Course: Data Mining Pipeline
1.0
Reviewed May 6, 2023Course: Data Mining Pipeline
matt
Course: Data Mining Pipeline
1.0
Reviewed Mar 9, 2023Course: Data Mining Pipeline
Caroline
Course: Data Mining Pipeline
1.0
Reviewed Sep 26, 2024Course: Data Mining Pipeline
Kevin
Course: Data Mining Pipeline
1.0
Reviewed Jun 24, 2023Course: Data Mining Pipeline
George
Course: Data Mining Pipeline
1.0
Reviewed Jan 1, 2023Course: Data Mining Pipeline
Stanislav
Course: Data Mining Pipeline
2.0
Reviewed Aug 5, 2024Course: Data Mining Pipeline
Nathan
Course: Data Mining Pipeline
1.0
Reviewed Mar 22, 2022Course: Data Mining Pipeline
Silas
Course: Data Mining Pipeline
1.0
Reviewed Jan 10, 2023Course: Data Mining Pipeline
Christopher
Course: Data Mining Pipeline
1.0
Reviewed Jun 23, 2023Course: Data Mining Pipeline
Burt
Course: Data Mining Pipeline
3.0
Reviewed Jul 24, 2024Course: Data Mining Pipeline
عبدالله
Course: Data Mining Pipeline
3.0
Reviewed Dec 27, 2022Course: Data Mining Pipeline
THANIKANTI
Course: Data Mining Pipeline
5.0
Reviewed Aug 20, 2024Course: Data Mining Pipeline
KADAPA
Course: Data Mining Pipeline
4.0
Reviewed Sep 28, 2023Course: Data Mining Pipeline
Igor
Course: Data Mining Pipeline
1.0
Reviewed Aug 24, 2025Course: Data Mining Pipeline
G
Course: Data Mining Pipeline
5.0
Reviewed Sep 16, 2024Course: Data Mining Pipeline
Lauren
Course: Data Mining Pipeline
1.0
Reviewed Jan 24, 2026Course: Data Mining Pipeline
Dheeraj
Course: Data Mining Pipeline
5.0
Reviewed Mar 19, 2025Course: Data Mining Pipeline
Trinh
Course: Data Mining Pipeline
5.0
Reviewed Aug 16, 2025Course: Data Mining Pipeline