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Overview
The Data Mining Foundations and Practice Specialization 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.
Key facts
- 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.
What you'll learn
- Data mining pipeline: data understanding, preprocessing, warehousing
- Data mining methods: frequent patterns, classification, clustering, outliers
- Data mining project: project formulation, design, implementation, reporting
Skills you'll gain
- Supervised Learning
- Unsupervised Learning
- Machine Learning Algorithms
- Data Mining
Programme Structure
Courses include:
- Data Mining Pipeline
- Data Mining Methods
- Data Mining Project
Key information
Duration
- Part-time
- 2 months
- Flexible
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Mountain View, United States
Disciplines
Data Science & Big Data View 463 other Short Courses in Data Science & Big Data in United StatesWhat students do after studying
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Academic 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.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
- This short course is included with Coursera Plus subscription
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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