DP
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This course covers the end to end cycle suggested framework that can be useful not only in Data Science but also in other Research Projects that manage information to create and deploy a solution.
JR
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It is a very important course to understand the procedures and thought processes behind data science. I strongly recommend it to those who are unfamiliar with data science or reserach methodology.
By Anuj M
•Jul 8, 2019
Hi I found this course useful though there can be better example than food and linking of python at lab rite away was more confusing
By Kristin R
•Dec 13, 2018
This could've been condensed down immensely, but I suppose it's something you deal with when sorting through data for data science.
By Hanieh I
•May 5, 2020
The course was very informative I just wish it went into a little more detail of the statistical tests used in the methodologies.
By Liza V
•Jan 27, 2020
It's quite clear and interesting course. What lack is a reference to additional reading to give more overview about the subject.
By Pavel N
•Nov 21, 2021
It would be great if it's possible to add labs with predictive and descriptive models to this course (not only classification).
By J. O M
•Mar 2, 2020
The case study used was difficult to understand.
The lab tutorial too were not detailed.
However the course is very interesting .
By Anup J M
•Sep 19, 2019
I really liked the course content. Although i would love see another case study added into the course for greater understanding
By Imran R
•Jan 7, 2019
Very informative course with the exercises designed to cover complete data science methodology based on the Mr. John Rollins.
By Sharvari U
•Oct 6, 2019
Examples shared to explain the methodology could have been a bit easy so every domain person can perceive it equally well.
By Serdar M
•Oct 25, 2018
the final assignment is too open-ended. no exact questions and answers. everything is left to understanding of your peers.
By Maria N W
•Jun 22, 2021
Methodology is clear. I liked the Python exercise with the recipes. I could see how it could apply to other industries.
By Zezhou J
•Sep 27, 2018
Well-structured course with crystal clear explanations. Case study is intriguing. However lectures are still a bit dry.
By Mohammad R
•Aug 28, 2022
This course wouldn't be helpful at all if it wasn't in the data science program. This couldn't be an individual course
By Yash T
•Oct 28, 2021
The example of Congestive Heart Failure given in video to explain data science methodology is difficult to understand.
By Yoshihide J S
•Jan 8, 2021
I feel we need slightly more case study, not enough case study example! So, understanding the meaning "methodology".
By Nikhil J
•Jul 4, 2020
It gave a nice overview of how things flow in a data scientist mind. Provides a framework to think approach problems.
By Stanley Y
•Nov 29, 2019
Peer-reviewed exercises often result in inconsistent feedback! The course requires a more rigorous method of grading.
By Emilio B
•May 7, 2020
Buen curso aunque a mi parecer un poco monótono y repetitivo a veces. No tenÃa muy claras las explicaciones a veces.
By shibu p
•Sep 24, 2019
I learned a lot on Data science methodology. Now i know how data scientist thing and work. It was a good experience.
By Yifan H
•Aug 22, 2019
love the food recipe case! i am not familiar with clinical case but the food recipe case helped me learn the theory.
By David A
•Jul 15, 2019
A good introduction to the process a data science uses to answer complicated problems. I found it very interesting.
By Shubham V
•Sep 12, 2021
Content and learning is good, but you can improve quality of images used in videos. Sometimes text was not readable
By Jeevan K
•May 19, 2020
I found it difficult to understand the Data understanding step in the course.
Examples can be little in normal terms
By Amogh K
•Mar 24, 2020
The final assessment is very confusing for starters and needs to be more in line with the material actually taught.
By Praveen K
•Oct 13, 2019
This course should have been in the later stages. It is too early to understand all what the instructor has to say.