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Data Mining Pipeline
  • Level Professional
  • Duration 22 hours
  • Course by University of Colorado Boulder
  • Offered by

About

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

Modules

Course Introduction

    • 2 Videos
    • 3 Readings
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2 Videos

  • Meet Your Instructor!
  • Preparing for this Specialization

3 Readings

  • Earn Academic Credit for Your Work!
  • Course Support
  • About this Course

Introduction to Data Mining

    • 3 Videos
    • 1 Discussion
    • 1 PeerReview
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1 Peer Review

  • Data Mining Example

1 Discussions

  • Let's Get to Know Each Other!

3 Videos

  • Data Mining: Four Views
  • Data View and Application View
  • Knowledge View and Technique View

Introduction to Data Mining Pipeline

    • 3 Videos
    • 1 PeerReview
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1 Peer Review

  • Data Mining Issues

3 Videos

  • Data Mining Pipeline
  • Data Mining Examples
  • Data Mining: Major Issues, Ethics, Resources

Objects & Attributes, Statistics, Visualization

    • 2 Videos
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2 Videos

  • Data Objects, Attributes, Statistics
  • Data Visualization

Data Similarity

    • 4 Videos
    • 1 Programming
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1 Programming

  • Data Understanding

4 Videos

  • Similarity for Normal and Binary Attributes
  • Similarity for Ordinal, Numeric, Mixed Attributes
  • Data Similarity Case Study
  • Example: Air Quality Sensing Data

Data Cleaning, Data Integration

    • 3 Videos
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3 Videos

  • Data Quality Issues and Causes
  • Data Cleaning, Data Integration
  • Correlation Analysis

Data Transformation, Data Reduction

    • 3 Videos
    • 1 Programming
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1 Programming

  • Data Preprocessing

3 Videos

  • Data Normalization
  • Discretization, Attribute Selection
  • Dimensionality/Numerosity Reduction

Data Warehouse, Data Cube and OLAP

    • 2 Videos
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2 Videos

  • Data Warehousing, OLTP vs. OLAP
  • Data Warehouse, Data Cube

Data Cube Computation, Data Warehouse Architecture

    • 2 Videos
    • 1 Programming
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1 Programming

  • Data Warehousing

2 Videos

  • Data Cube Computation
  • Data Warehouse Architecture

Auto Summary

Discover the Data Mining Pipeline course focused on Big Data and Analytics, taught by Coursera. Learn essential steps like data understanding, preprocessing, warehousing, modeling, and evaluation. Ideal for recent graduates and professionals, this course is part of CU Boulder's MS in Data Science or Computer Science, featuring short 8-week sessions and pay-as-you-go tuition. Enroll now to advance your career in data science!

Qin (Christine) Lv
Instructor

Qin (Christine) Lv