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Retour à Foundations of Data Science: K-Means Clustering in Python

Avis et commentaires pour d'étudiants pour Foundations of Data Science: K-Means Clustering in Python par Université de Londres

4.7
étoiles
371 évaluations
119 avis

À propos du cours

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....

Meilleurs avis

GK
31 août 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
3 juin 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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101 - 119 sur 119 Avis pour Foundations of Data Science: K-Means Clustering in Python

par Jesus R

25 sept. 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.

par Soumya S

1 mai 2020

It is a very detailed and well planned course. However, there could have been a few lectures at the end on training set, testing set etc.

par Leonard J

9 août 2020

Very good course to help you understand the basics of data science, the videos are short so will not cover everything you need

par Chintoo K

31 mai 2020

It was a great journey to get through it. Thanks a lot to all the instructors for their valuable job and effort :)

par Jason A

18 févr. 2020

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

par Gangolli, V

20 sept. 2020

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

par Peggy L

5 avr. 2021

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

par Yeung K Y

14 oct. 2020

Good content and I would recommend my friends for it.

par Bhawna D

24 sept. 2019

More time should be given in the coding part.

par Leo G

28 juin 2021

A​n introductory course all together.

par Jaison M

30 avr. 2020

Very good if new to data science

par DIVYESH M

12 juil. 2020

Nice course for New learner

par KASIVAJHULA S K

13 mai 2020

GREAT COURSE!

par Jonathan B

15 déc. 2020

All the statistics and k-Means algorithms are well explained, but there is much missing guidance on how to conduct the final project.

par Ryan N

27 sept. 2020

Mathematics taught is very abstract. Not many practice examples and linkage to practical side. Not much guidance on guided projects.

par Anton S

17 août 2019

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

par Gagan P P

21 mai 2020

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

par Margaret M L

20 janv. 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?