This course is part of the Data Mining Foundations and Practice Specialization

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stars

15 ratings

Qin (Christine) Lv

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Offered By

Data Mining Foundations and Practice SpecializationUniversity of Colorado Boulder

About this Course

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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 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.

Course logo image courtesy of Francesco Ungaro, available here on Unsplash: https://unsplash.com/photos/C89G61oKDDA

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 1 of 3 in the

Data Mining Foundations and Practice Specialization

Intermediate Level

data science professionals or domain experts, some experience working with data

Approx. 21 hours to complete

English

What you will learn

By the end of this course, you will be able to identify the key components of the data mining pipeline and describe how they're related.
You will be able to identify particular challenges presented by each component of the data mining pipeline.
You will be able to apply techniques to address challenges in each component of the data mining pipeline.

Skills you will gain

Data Pre-Processing
Data Warehousing
data understanding
data mining pipeline

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 3 in the

Data Mining Foundations and Practice Specialization

Intermediate Level

data science professionals or domain experts, some experience working with data

Approx. 21 hours to complete

English

Instructor

Instructor rating

1.25/5 (6 Ratings)

Qin (Christine) Lv

Associate Professor

Computer Science

5,075 Learners

3 Courses

Offered by

University of Colorado Boulder

Syllabus - What you will learn from this course

Week1

Week 1

6 hours to complete

Data Mining Pipeline

6 hours to complete

2 videos (Total 88 min), 3 readings, 2 quizzes

Week2

Week 2

5 hours to complete

Data Understanding

5 hours to complete

2 videos (Total 71 min)

Week3

Week 3

5 hours to complete

Data Preprocessing

5 hours to complete

2 videos (Total 77 min)

Week4

Week 4

5 hours to complete

Data Warehousing

5 hours to complete

2 videos (Total 54 min)

About the Data Mining Foundations and Practice Specialization

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

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Data Mining Pipeline

About this Course

What you will learn

Skills you will gain