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Data Mining Pipeline

This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehousing, data modeling,...

By Qin (Christine) Lv on Coursera

About This Course

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. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder Course logo image courtesy of Francesco Ungaro, available here on Unsplash: https://unsplash.com/photos/C89G61oKDDA

Topics Covered

Frequently Asked Questions

How much does Data Mining Pipeline cost?

Visit the Data Mining Pipeline course page for current pricing and available discounts.

Who teaches Data Mining Pipeline?

Data Mining Pipeline is taught by Qin (Christine) Lv, University of Colorado Boulder.

What skill level is Data Mining Pipeline for?

This course is designed for all levels learners.

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Students0
DurationSelf-paced
LevelAll Levels
Languageen
PlatformCoursera