Data Mining Pipeline

Data Mining Pipeline

This course is part of Data Mining Foundations and Practice Specialization

Instructor: Qin (Christine) Lv

Access provided by Emirates Water & Electricity Co.

12,250 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

111 reviews

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

111 reviews

Intermediate level

Recommended experience

2 weeks to complete

at 10 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.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

1 assignment

Taught in English

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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.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in 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

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 videos6 readings1 assignment2 peer reviews1 discussion prompt

8 videos Total 103 minutes

Meet Your Instructor! 5 minutes
Preparing for this Specialization 9 minutes
Data Mining: Four Views 9 minutes
Data View and Application View 16 minutes
Knowledge View and Technique View 17 minutes
Data Mining Pipeline 14 minutes
Data Mining Examples 18 minutes
Data Mining: Major Issues, Ethics, Resources 15 minutes

6 readings Total 60 minutes

Earn Academic Credit for Your Work! 10 minutes
Course Support 10 minutes
About this Course 10 minutes
Assessment Expectations 10 minutes
Introducing Honorlock for For-Credit Exam Proctoring 10 minutes
AI Citation and Acknowledgement 10 minutes

1 assignment Total 5 minutes

AI Policy Quiz 5 minutes

2 peer reviews Total 210 minutes

Data Mining Example 60 minutes
Data Mining Issues 150 minutes

1 discussion prompt Total 10 minutes

Let's Get to Know Each Other! 10 minutes

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

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Build toward a degree

This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹

Instructor

Instructor ratings

(29 ratings)

Qin (Christine) Lv

University of Colorado Boulder

3 Courses 16,844 learners

Offered by

University of Colorado Boulder

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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.

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