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.
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Foundations of Data Science: K-Means Clustering in Python
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Instructors: Dr Matthew Yee-King
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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
Details to know
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39 assignments
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There are 5 modules in this course
This week we will introduce you to the course and to the team who will be guiding you through the course over the next 5 weeks. The aim of this week's material is to gently introduce you to Data Science through some real-world examples of where Data Science is used, and also by highlighting some of the main concepts involved.
What's included
9 videos4 assignments3 discussion prompts
What's included
11 videos4 readings10 assignments1 peer review1 ungraded lab
What's included
16 videos10 readings15 assignments
What's included
8 videos6 readings7 assignments1 peer review
What's included
9 videos3 readings3 assignments3 peer reviews5 discussion prompts
Instructors
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Learner reviews
705 reviews
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Reviewed on Jan 2, 2022
This course was excellent. Though I already knew the concepts in this course and the programing skills, it has inspired me to 100% take the MSC provided. Excellent lectures. Just Excellent.
Reviewed on Jun 3, 2019
This course is at right level for a beginner (python and analytics) while going into details around K means clustering
Reviewed on Jun 28, 2020
Very interesting course! The lecturers explain concepts thoroughly which makes the concepts easy to understand even for people without much knowledge in Data Science
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