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

Foundations of Data Science: K-Means Clustering in Python

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

Instructors: Dr Matthew Yee-King

71,947 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.6

(685 reviews)

Beginner level

Recommended experience

Flexible schedule
Approx. 29 hours
Learn at your own pace
95%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.6

(685 reviews)

Beginner level

Recommended experience

Flexible schedule
Approx. 29 hours
Learn at your own pace
95%
Most learners liked this course

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 assignments

Taught in English

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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

Instructor ratings
4.6 (290 ratings)
Dr Matthew Yee-King
University of London
21 Courses410,754 learners
Dr Betty Fyn-Sydney
University of London
1 Course71,947 learners

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4.6

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