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

4.7
stars
171 ratings
56 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

AH

Jun 04, 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.

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.

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1 - 25 of 56 Reviews for Foundations of Data Science: K-Means Clustering in Python

By Nilson S d C

May 17, 2020

This course gives us a good balance between theory and practice. I wish there was an intermediate or advanced level to continue.

By Katlin S

Feb 05, 2020

The course was very well layed out and divided into short lessons. Things were explained and I found them easy to follow. There was also plenty of focus on practice. Assignments were peer reviews which made the process quite fast. The assignment made me understand the bigger picture and pushed me to do further reading/research. I very much enjoyed the experience

The only problem I had was with the app. I could not use it to upload, submit quizzes or properly view peer's work or my own feedback.

By Stephen K

Oct 22, 2019

I felt that the instructors were passionate about the subject and it made me want to learn more. The course assumes that you don't know any python, which was good for me as that was exactly my situation when I started. However, if students did have a more advanced knowledge of data science concepts and python they could show this off in the assignments.

By Uriel C

Apr 07, 2020

This is a very good and useful course for learning about the basics of data science. I highly recommend it if you want to start learning about this field. Basics skills of coding are recommended

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 federico a

Oct 25, 2019

I liked it, very usefull and objective guide to implemt the algorithm, I also liked the format, many short videos wich is great to keep concentration

By Juan D C N

Apr 23, 2020

Excellent course! It was well distributed, videos and theorical content, and then, practical videos and cases. Recommended!

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 Navya S

Apr 24, 2020

It is a very apt course for beginners. All the concepts have been taught and discussed properly

By Jesper O

Apr 18, 2020

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

By Amy S

Feb 22, 2020

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

By Harshit R

Apr 26, 2020

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

By Ankara s

Apr 09, 2020

Good

By KUTLU

Apr 17, 2020

i am giving this note because they read theirs textes. it is not a teaching method. ı could read myself as well. i don't' understand why they do like this. in addition, the project is not well planned.

By Tarik S

Jun 21, 2020

Great course. It involves a lot of independent work but that is the nature of learning to programme in any language. Once you get down to doing the work the course is enjoyable and the learning curve is steep and therefore productive. Time well invested

By Austin T L H

Jun 04, 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.

By Sevinc S

Jun 30, 2020

A well presented and interesting course. It would have been good to have some more complex examples with the thinking behind them - the exploratory bit/intelligent bit of the process.

By Marianne K M

Jun 29, 2020

Very interesting course! The lecturers explain concepts thoroughly which makes the concepts easy to understand even for people without much knowledge in Data Science

By Sanmesh S S

May 31, 2020

Amazing Course. I got the basic understanding of K-means clustering also assignments are very good and tricky also

By Emi B

Jun 26, 2020

It gives you a really complete first glimpse into the clustering and data analysis world! Great teachers too!

By SAEED M A

May 13, 2020

I learned a more about Data Science K-Mean Clustering. very good design and practical.

By Muhammad A N

May 11, 2020

Found the course to be concise and informative; kept my interest going till the end

By Tinashe N

Jul 01, 2020

Well organised and the flow of information is superb, meets the objective by far.

By Maria F F

May 14, 2020

100% Recommended, Is a good tool if you do not know anything about Python (as me)

By Ihsan N R H

Jun 17, 2020

This course its good if you want to learn about data science K-Means Clustering