Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government.
Foundations of Data Science: K-Means Clustering in Python
Foundations of Data Science: K-Means Clustering in Python
Instructors: Professor Matthew Yee-King
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Gain insight into a topic and learn the fundamentals.
735 reviews
Beginner level
Recommended experience
Flexible schedule
3 weeks at 10 hours a week
Learn at your own pace
95%
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What you'll learn
Define and explain the key concepts of data clustering
Demonstrate understanding of the key constructs and features of the Python language.
Implement in Python the principle steps of the K-means algorithm.
Design and execute a whole data clustering workflow and interpret the outputs.
Skills you'll gain
Tools you'll learn
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Taught in English
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There are 5 modules in this course
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Showing 3 of 735
SS
Reviewed on Jun 29, 2020
A well presented and interesting course. It would have been good to have some more complex examples with the thinking behind them - the exploratory bit/intelligent bit of the process.
PM
Reviewed on Dec 19, 2022
Overall, a great experience but labs could have been better, and few instructors were not very detailed in their approach.
GK
Reviewed on Aug 31, 2021
This course has great potential for future Data Scientists and it gives a breif explination of what we are dealing in the companies by giving us real life problems and making us solve those problems.
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