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

Qin (Christine) Lv

Offered By

Part of the Master of Science in Data Science degree

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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

100% online

Start instantly and learn at your own schedule.

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

Subtitles: 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-ProcessingData Warehousingdata understandingdata 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.

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

Subtitles: English

Instructor

Qin (Christine) Lv

Associate Professor

Computer Science

1,038 Learners

3 Courses

Offered by

University of Colorado Boulder

CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Data Science from University of Colorado Boulder. If you are admitted to the full program, your courses count towards your degree learning.

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Syllabus - What you will learn from this course

Week

Week 1

5 hours to complete

Data Mining Pipeline

This module provides an introduction to data mining and data mining pipeline, including the four views of data mining and the key components in the data mining pipeline.

5 hours to complete

2 videos (Total 88 min), 1 reading, 2 quizzes

Week

Week 2

5 hours to complete

Data Understanding

This module covers data understanding by identifying key data properties and applying techniques to characterize different datasets.

5 hours to complete

2 videos (Total 71 min)

Week

Week 3

5 hours to complete

Data Preprocessing

This module explains why data preprocessing is needed and what techniques can be used to preprocess data.

5 hours to complete

2 videos (Total 77 min)

Week

Week 4

5 hours to complete

Data Warehousing

This module covers the key characteristics of data warehousing and the techniques to support 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.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.

Data Mining Pipeline