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.
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.
par 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.
par 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.
par 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
par Chintoo K•
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•
Good intro into K-means clustering. Some great introductory math tutorials and basic python programming.
par Gangolli, V•
It is a good one for the beginner who is ready to give dedicated time.
par Peggy L•
useful. it will be better if you have some basic knowledge on python
par Yeung K Y•
Good content and I would recommend my friends for it.
par Bhawna D•
More time should be given in the coding part.
par Leo G•
An introductory course all together.
par Jaison M•
Very good if new to data science
par DIVYESH M•
Nice course for New learner
par KASIVAJHULA S K•
par 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.
par Ryan N•
Mathematics taught is very abstract. Not many practice examples and linkage to practical side. Not much guidance on guided projects.
par Anton S•
Good introduction to k-means clustering using Python. Easy for follow.
par Gagan P P•
Good course.. But self study also needed...
par 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?