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Opiniones y comentarios de aprendices correspondientes a Foundations of Data Science: K-Means Clustering in Python por parte de Universidad de Londres

4.7
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234 calificaciones
76 revisiones

Acerca del Curso

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....

Principales revisiones

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 de 76 revisiones para Foundations of Data Science: K-Means Clustering in Python

por 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.

por 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.

por 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.

por 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

por 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.

por 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

por Juan D C N

Apr 23, 2020

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

por Aditya B

Jun 04, 2019

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

por Navya S

Apr 24, 2020

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

por Jesper O

Apr 18, 2020

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

por Amy S

Feb 22, 2020

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

por Harshit R

Apr 26, 2020

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

por Ankara s

Apr 09, 2020

Good

por 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.

por mike

Aug 27, 2020

Learned much from this course thanks to all great instructors. It will be better if learners have some basic Python knowledge otherwise may have some difficulty in the coding of the assignments. As with all MOOC there are always rooms for improvement. For this course my thinking is that some sections need to be revised for better clarity e.g. the Mathematical explanation on Euclidean distance where it can be overwhelming and the learners may find it difficult to relate it relevance to K-Means amongst all the mathematical jargon. Overall this course provides good insight for beginners into understanding K-Means using Python, and an overview of performing proper data science project.

por Kaushik G

Aug 31, 2020

Excellent and very well designed course. The way the course exponentially takes you from the very basics of the topic to a certain level of mastery is commendable. If you know the basics of data science and Python programming, this course can easily be completed in less than a week. The peer reviews can be more productive if fellow learners actively participate more often and leave valuable feedback, rather than only responding to mandatory radio buttons for feedback.

por Raushan U

Jul 20, 2020

I would highly recommend the course to those who have no background in Data Science. I started without any knowledge about Python and upgraded it with the help of this course. Videos are short and informative. Assignments are short and related to the videos discussed before. It's easy to finish the course before deadlines.

The only drawback is that the course doesn't have any Financial Aid.

por Vicky P

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.

por Rudresh R V

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.

por edajima h

Jul 16, 2020

I think this is a very good course for beginners in Data Science and Python. I know how to implement K-means algorithm but wanted to learn Python, so I took this course. It is well organized, and videos are short and concise. I am looking forward to more intermediate / advanced courses of this.

por 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

por 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.

por 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.

por Benedict C O

Jul 04, 2020

Highly recommended to anyone who wants to delve into data science. The instruuctors, the universities and Coursera team are well dedicated and the course is of high quality.

por 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