This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehousing, data modeling, interpretation and evaluation, and real-world applications.
Data Mining Pipeline
Data Mining Pipeline
This course is part of Data Mining Foundations and Practice Specialization
Instructor: Qin (Christine) Lv
Sponsored by Coursera Learning Team
8,613 already enrolled
Gain insight into a topic and learn the fundamentals.
3.7
(77 reviews)
Intermediate level
Recommended experience
21 hours to complete
3 weeks at 7 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Identify the key components of the data mining pipeline and describe how they're related.
Identify particular challenges presented by each component of the data mining pipeline.
Apply techniques to address challenges in each component of the data mining pipeline.
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Taught in English
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This course is part of the Data Mining Foundations and Practice Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
This week provides you with an introduction to the Data Mining Specialization and this course, Data Mining Pipeline. As you begin, you will get introduced to the four views of data mining and the key components in the data mining pipeline.
What's included
8 videos3 readings2 peer reviews1 discussion prompt
This week covers data understanding by identifying key data properties and applying techniques to characterize different datasets.
What's included
6 videos1 programming assignment
This week explains why data preprocessing is needed and what techniques can be used to preprocess data.
What's included
6 videos1 programming assignment
This week covers the key characteristics of data warehousing and the techniques to support data warehousing.
What's included
4 videos1 programming assignment
Instructor
Instructor ratings
2.5 (20 ratings)Offered by
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3.7
77 reviews
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JG
5
Reviewed on 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.
Recommended if you're interested in Data Science
University of Colorado Boulder
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University of Colorado Boulder
University of Colorado Boulder
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