课程详情

What you will learn
Data mining pipeline: data understanding, preprocessing, warehousing
Data mining methods: frequent patterns, classification, clustering, outliers
Data mining project: project formulation, design, implementation, reporting
B​y 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.
Skills you will gain
work through the data mining pipeline
data mining project design and implementation
apply and evaluate data mining methods
Data Pre-Processing
Data Warehousing
data understanding
data mining pipeline
outlier analysis
clustering
classification
model evaluation
frequent pattern analysis
About this Specialization
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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
Applied Learning Project
There are programming assignments that cover specific aspects of the data mining pipeline and methods. Furthermore, the Data Mining Project course provides step-by-step guidance and hands-on experience of formulating, designing, implementing, and reporting of a real-world data mining project.
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Intermediate Level
Intermediate Level
Learners should have some experience working with data, Python programming, data structures and algorithms, and basic concepts of probability.
Hours to complete
Approximately 3 months to complete
Suggested pace of 7 hours/week
Available languages
English
Subtitles: English
Shareable Certificate
Shareable Certificate
Earn a Certificate upon completion
100% online courses
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Flexible Schedule
Set and maintain flexible deadlines.
Intermediate Level
Intermediate Level
Learners should have some experience working with data, Python programming, data structures and algorithms, and basic concepts of probability.
Hours to complete
Approximately 3 months to complete
Suggested pace of 7 hours/week
Available languages
English
Subtitles: English

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