Learner Reviews & Feedback for Foundations of Data Science: K-Means Clustering in Python by University of London
About the Course
Top reviews
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.
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.
76 - 100 of 100 Reviews for Foundations of Data Science: K-Means Clustering in Python
By VIJAYA R
•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.
By HYEIN P
•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
•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 Justin M J
•I would highly recommend this course for any beginners. it simply suits both the first timers and people who wish to further existing knowledge and understanding of Python and data science to another level. enjoyable homebased learning.
By Daniel e
•First 4 weeks very good (you learn enough and there are interesting topics), last week very "backloaded" half the course I would say. Also you dont get to do your ow project but is given a topic which i did not like. very good overall.
By Jesus R
•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 Soumya S
•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.
By Leonard J
•Very good course to help you understand the basics of data science, the videos are short so will not cover everything you need
By Chintoo K
•It was a great journey to get through it. Thanks a lot to all the instructors for their valuable job and effort :)
By Jason A
•Good intro into K-means clustering. Some great introductory math tutorials and basic python programming.
By Gangolli, V
•It is a good one for the beginner who is ready to give dedicated time.
By Peggy L
•useful. it will be better if you have some basic knowledge on python
By Yeung K Y
•Good content and I would recommend my friends for it.
By Bhawna D
•More time should be given in the coding part.
By Jaison M
•Very good if new to data science
By DIVYESH M
•Nice course for New learner
By KASIVAJHULA S K
•GREAT COURSE!
By Jonathan B
•All the statistics and k-Means algorithms are well explained, but there is much missing guidance on how to conduct the final project.
By Ryan N
•Mathematics taught is very abstract. Not many practice examples and linkage to practical side. Not much guidance on guided projects.
By Anton S
•Good introduction to k-means clustering using Python. Easy for follow.
By Naveed K
•It's a good course but data cleaning should also be included...
By Gagan P P
•Good course.. But self study also needed...
By Margaret M L
•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?
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