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

4.6
stars
642 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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26 - 50 of 198 Reviews for Foundations of Data Science: K-Means Clustering in Python

By Aditya B

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Jun 3, 2019

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

By Jesper O

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Apr 18, 2020

Great introduction to clustering. Week 5 material could be improved - not as good as 1-4.

By Amy S

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Feb 22, 2020

Really enjoyable and well thought through. As someone new to data science I learnt a lot!

By Harshit R

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Apr 26, 2020

Thanks for this course. It was good experience and content of course was also very nice.

By Ahmad Z A B A

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Jul 6, 2023

Great for starter and those who have no experience in data science and phyton.

By ILTIMAS K

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Jul 7, 2023

I really enjoyed the course and learned a lot

By Ankara s

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Apr 9, 2020

Good

By Carles E M C

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Jun 11, 2021

The course is nice and well explained. Some of the mathematical concepts are explained into more detail than necessary for the scope of the course, and at the same time with not enough detail to understand them properly. Also, I expected the course to show some professional software, but it only touches Python. Still, I enjoyed the course and I think it does it's job as an itroduction to the subject.

By Daniel W S

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Dec 23, 2020

I was impressed by the amount of informative, relevant and in-depth material, taught and built up form a very basic level. The video lectures and practical exercises have really helped to cement the material covered in this course. In areas, there are quite a few mistakes (content, wording, etc), which can be confusing and come across as a bit sloppy.

By HYEIN P

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May 10, 2020

It was not fully explained how to use Python, therefore I should have looked for the more information through internet by myself.

However, it was quite interesting to understand why data science could be important and how to use with K-means clustering.

By Colin A

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Aug 16, 2020

Overall what you get for the price is about right. Sometimes there are glaring gaps in the presentation of concepts, and how sections fit together. In the end it served its purpose to me - to see if I want to continue exploring data science a a field.

By Jesus R

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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 Jason A

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Feb 18, 2020

Good intro into K-means clustering. Some great introductory math tutorials and basic python programming.

By Gangolli, V

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Sep 20, 2020

It is a good one for the beginner who is ready to give dedicated time.

By Peggy L

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Apr 5, 2021

useful. it will be better if you have some basic knowledge on python

By Bhawna D

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Sep 24, 2019

More time should be given in the coding part.

By Gagan P P

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May 21, 2020

Good course.. But self study also needed...

By Margaret M L

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Jan 20, 2021

You should be able to transcribe the code which is presented into Jupyter Notebooks as is. This is now the second time I have done so and I am guessing some of the needed code was left out as the code does not work. How can students be expected to complete assignments when the Instructor's code is not reproducible?

By Nikos B

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Nov 2, 2023

It is one of the best-organized and mathematical-oriented courses in Data Science and the general concept of Unsupervised Statistical Learning. After successfully attending and doing the capstone project, I could say that it is an intensive coursework-micro master of the topics that are covered. Above all, it is not an introductory course in Statistics. It requires some important basis in Mathematics and Statistics as well to understand some special topics of Metrics Topology that help to visualize in your mind the algorithm of k-means. Thank you, Coursera and partners, for this wonderful journey in the Mathematics of Machine Learning.

P.S. Peer assignments are completed on time only if people try to review each other's assignment.

By Stergios T

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May 28, 2023

This specific online coursera lesson, the way that it was designed, presented and delivered was a huge and great first step for me personally into learning and becoming familiar with the field of data science and i would like to thank all the Factors and the professors of the University of London for achieving this kind of online data science structure lesson. All of their videos, lectures and programming lessons were very interesting, informative , well understood and i would also like suggest anyone that is thinking of deepening his knowledge into this field, to follow this specific lesson.

By Nicolás A P L

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Feb 1, 2024

I would like to thank the entire team at the University of London for providing this excellent introductory course on the use of the k-means algorithm. Perhaps it would be a good idea to include concepts such as the elbow method, which aims to determine the ideal number of clusters, and the confusion matrix for model evaluation. Thank you for everything, and you have significantly encouraged me to continue on my path in data science.

By Mokone L

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May 17, 2022

Method of instruction was easy to understand yet the content was very rich. The last project really openned my thinking in many respects. It pushed me to read a lot of other materials beyond the scope of the course.

Resetting deadlines fascility in this course is very helpful. I was during this course not able to attend course due to work commitments but I was able to reset deadlines and resume. It was great.

By Anselmo A

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Jul 11, 2022

I totally recommend the great excellence of the course material, methods, tests and instructors. Thanks Matthew Yee-King, Betty Fynsydney and Dr. Larisa Soldatova. In this course we can learn more about K-Means Clustering, Statistic, Dimensional and Multidimensional Mean, Variance, Standard Deviation, Normalisation, Outliers, Numpy, Matplotlib and Pandas, where every thing was done using Python.

By Vicky

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Sep 12, 2020

The course content is great. I especially enjoyed Week 4—the lecturer was concise and engaging. There are lots of people plagiarising others' work by screenshotting their charts though and re-submitting their work which is sad. This course would benefit from a summary at the end of week 5 explaining what conclusions we might or should have come to.

By Rudresh R V

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Jul 30, 2020

This is a perfect course for those who just dove into the ocean of data science. This course teaches you with the very beginning and you can easily tackle everything even you don't know anything about data science. I highly recommend everyone to start with this foundation level course if you want to excel in the field fo Data Science.