University of Colorado Boulder

Data Mining Pipeline

This course is part of Data Mining Foundations and Practice Specialization

Taught in English

Some content may not be translated

Qin (Christine) Lv

Instructor: Qin (Christine) Lv

6,336 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

3.3

(43 reviews)

Intermediate level

Recommended experience

21 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

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.

Details to know

Shareable certificate

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Course

Gain insight into a topic and learn the fundamentals

3.3

(43 reviews)

Intermediate level

Recommended experience

21 hours (approximately)
Flexible schedule
Learn at your own pace
Progress towards a degree

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

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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  • Develop job-relevant skills with hands-on projects
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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
2.0 (13 ratings)
Qin (Christine) Lv
University of Colorado Boulder
3 Courses8,892 learners

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Recommended if you're interested in Data Analysis

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3.3

43 reviews

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JG
5

Reviewed on Oct 1, 2023

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