Endorsed by
Coursera 4.3 (9)
Overview
The Data Mining Foundations and Practice course offered by Coursera in partnership with University of Colorado Boulder 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.
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.
What You Will Learn:
- Data mining pipeline: data understanding, preprocessing, warehousing
- Data mining project: project formulation, design, implementation, reporting
- Data mining methods: frequent patterns, classification, clustering, outliers
Skills You Will Gain:
- Apply and evaluate data mining methods
- Work through the data mining pipeline
- Data mining project design and implementation
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Visit programme websiteProgramme Structure
Courses include:
- Data Mining Pipeline
- Data Mining Methods
- Data Mining Project
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 2 months
- Flexible
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Disciplines
Data Science & Big Data View 592 other Short Courses in Data Science & Big Data in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Intermediate level
- Learners should have some experience working with data, Python programming, data structures and algorithms, and basic concepts of probability.
Make sure you meet all requirements
Visit programme websiteTuition Fee
To always see correct tuition fees
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International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 months.
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Funding
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.
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