University of Colorado Boulder - Data Mining Pipeline
- Offered byCoursera
Data Mining Pipeline at Coursera Overview
Data Mining Pipeline
at Coursera
Duration | 21 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Mining Pipeline at Coursera Highlights
Data Mining Pipeline
at Coursera
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level data science professionals or domain experts, some experience working with data
- Approx. 21 hours to complete
- English Subtitles: English
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Data Mining Pipeline at Coursera Course details
Data Mining Pipeline
at Coursera
Skills you will learn
More about 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.
- 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.
Data Mining Pipeline at Coursera Curriculum
Data Mining Pipeline
at Coursera
Data Mining Pipeline
Introduction to Data Mining
Introduction to Data Mining Pipeline
Course Information
Data Understanding
Objects & Attributes, Statistics, Visualization
Data Similarity
Data Preprocessing
Data Cleaning, Data Integration
Data Transformation, Data Reduction
Data Warehousing
Data Warehouse, Data Cube and OLAP
Data Cube Computation, Data Warehouse Architecture
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