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

4.6
stars
695 ratings

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

GK

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.

AH

Jun 3, 2020

I love this course as it gives me the foundations of learning the Python coding program and relevant statistical methods that used for data analysis. It's really interesting course to attend to.

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151 - 175 of 208 Reviews for Foundations of Data Science: K-Means Clustering in Python

By Fan K N

•

Feb 12, 2020

Excellent course !!!

By josue j G F

•

Jan 8, 2025

A excellent course!

By Ngo L M

•

Dec 7, 2022

Worth every penny!

By Saami S

•

Jul 24, 2022

excellent course!

By Paul L

•

Jul 13, 2020

Very good quality.

By Rania Y

•

Feb 21, 2024

It's great course

By pritee k

•

Jun 23, 2021

very informative

By Harsh P

•

Mar 29, 2020

Amazing Course!

By Miguel H

•

Aug 7, 2022

Great course!!

By Naeema T

•

Jul 22, 2020

amazing course

By WANG Y J

•

May 8, 2021

useful course

By Gerald D

•

Nov 27, 2020

Great course!

By NHẤT Đ M

•

Nov 11, 2024

greatttttttt

By Silvia M R

•

Feb 14, 2023

Excellent!!!

By Jocerose G

•

Jun 23, 2024

Thank u all

By hongsu

•

Jun 17, 2022

good course

By Josabet A A G

•

Jul 2, 2021

Good Course

By Lina J

•

Oct 26, 2023

Excellent!

By Victor C

•

Oct 11, 2023

Excellent

By Amin

•

Jan 14, 2020

Thank you

By Emma R

•

Oct 26, 2023

MUY UTIL

By Ardiansyah R

•

Sep 18, 2022

Best

By Полина К

•

Apr 22, 2023

It's perfect course, so precise videos and transcription! I express my gratitude to all the tutors and other members of a team who took part in course creation. You did really great job!

Note the course is not for the very beginner - you should understand smth in math, statistic and coding

What I didn't like at all in the course - a huge gap between detailed lessons and unexpectedly blurry explanations about how to write the final report. It seemed to me that I'd lost a week of lessons about doing the project somewhere

At least some examples or practise should be provided. I write marketing reports due to my current occupation but I got no idea whether my skills are appropriate in this case

By Harini B

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Aug 19, 2023

Basic concepts were explained in a systematic manner. Understanding was very easy with all those hands on exercises. End of course project was a struggle, needed some more ideas regarding the prediction of the model. Some more material regarding that would be of help. On the whole enjoyed the course, discussions were interesting and peer reviews helped understand other ways of answering the questions. Thank to the entire team of University of London and Coursera for this course.

By vijaya r

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May 25, 2020

This course starts from fundamental level. The instructors clearly explains statistical methods such as mean, variance, standard deviation, variance etc with python source code on a simple data set. Then they have explained plotting with labels and finally how to apply k-means clustering on bank note authentication dataset.