University of London
Foundations of Data Science: K-Means Clustering in Python
University of London

Foundations of Data Science: K-Means Clustering in Python

Taught in English

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64,375 already enrolled

Course

Gain insight into a topic and learn the fundamentals

Dr Matthew Yee-King
Dr Betty Fyn-Sydney
Dr Jamie A Ward

Instructors: Dr Matthew Yee-King

4.6

(642 reviews)

Beginner level

Recommended experience

29 hours to complete
3 weeks at 9 hours a week
Flexible schedule
Learn at your own pace

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.

Details to know

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Assessments

39 quizzes

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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 quizzes3 discussion prompts

What's included

11 videos4 readings10 quizzes1 peer review1 ungraded lab

What's included

16 videos10 readings15 quizzes

What's included

8 videos6 readings7 quizzes1 peer review

What's included

9 videos3 readings3 quizzes3 peer reviews5 discussion prompts

Instructors

Instructor ratings
4.6 (268 ratings)
Dr Matthew Yee-King
University of London
20 Courses387,351 learners
Dr Betty Fyn-Sydney
University of London
1 Course64,375 learners

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4.6

642 reviews

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ON
5

Reviewed on Apr 22, 2023

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5

Reviewed on Jun 28, 2020

AB
5

Reviewed on Jun 3, 2019

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