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Learner Reviews & Feedback for Foundations of Data Science: K-Means Clustering in Python by University of London

4.7
24 ratings
5 reviews

About the Course

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. This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks. You will consider these fundamental concepts on an example data clustering task, and you will use this example to learn basic programming skills that are necessary for mastering Data Science techniques. During the course, you will be asked to do a series of mathematical and programming exercises and a small data clustering project for a given dataset....

Top reviews

GR

Sep 10, 2019

184/5000\n\nConferences of very good quality, and the platform for practices is really useful to put the theory into practice. I recommend this course if you want to start in data science.

AA

Jun 04, 2019

This course is at right level for a beginner (python and analytics) while going into details around K means clustering

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1 - 5 of 5 Reviews for Foundations of Data Science: K-Means Clustering in Python

By Aditya

Jun 04, 2019

This course is at right level for a beginner (python and analytics) while going into details around K means clustering

By Guillermo A R

Sep 10, 2019

184/5000

Conferences of very good quality, and the platform for practices is really useful to put the theory into practice. I recommend this course if you want to start in data science.

By Jesus R

Sep 25, 2019

The lessons based on maths had a lot of text; it would have been better to base it more on graphics or imagery, since it was confusing to follow speech and text on video at the same time.

By Bhawna D

Sep 24, 2019

More time should be given in the coding part.

By Anton S

Aug 17, 2019

Good introduction to k-means clustering using Python. Easy for follow.