Learner Reviews & Feedback for Data Science Methodology by IBM
About the Course
Top reviews
NN
Jul 6, 2019
I like the way they provide sample with food preparation on each of the stage of data science methodology. Need to give more sample for the study case to give more insight and understanding.
JG
Nov 29, 2019
This was a clear and concise overview of the methodology and using the case study really helped (although sometimes it got a bit advanced considering this comes before actually learning models).
426 - 450 of 2,651 Reviews for Data Science Methodology
By Yair T
•Jun 30, 2022
Me gustó mucho porque nos lleva de la mano con las explicaciones sobre el curso general de un proyecto de este tipo.
By Riccardo B
•May 8, 2020
Nice Course, It was very well structured. I did some extra research to advance my knowledge of the different topics.
By Sunidhi K
•Feb 20, 2023
The course provided me the best understanding of data science methodology especially with hands on lab and quizzes.
By GK M
•May 2, 2021
Excellent course which gives in-dept knowledge of all stages of Data science Methodology. inspires to explore more.
By Eloise G
•Oct 29, 2020
Enjoyed the course and the slide presentations. Very informative. Lots of good material to use in future projects.
By Narayana P G
•Sep 21, 2020
A sublime introduction to all technical and business terms related to the methodology could help beginners like Me.
By David C
•Mar 8, 2020
A very good approach to iniciate in Data Science, the steps in CRISP - DM gave us the methodology to work with data
By man m s
•Jun 28, 2019
brilliant course, recomanded for every one, not inly deals with data science but also for any kind of office report
By Tomas M
•Nov 22, 2021
Basic, but excellent course, I would recommend it to anybody that looking to further their education in any field.
By Muhammad S
•Apr 11, 2020
Excellent course. Excellent jobs by the instructors to summarize all the techniques in a short package. Well done!
By Jeff S
•Feb 4, 2020
Good course. Its important to understand the methodology behind any science. This does a good job covering that.
By Naveenchandra M S
•Jul 9, 2019
In this course you will get insights on the all the stages which helps in applying these methodology in your work.
By Avinash S
•Dec 23, 2018
The topics covered in this course are really good. Without this course, the training in data science is incomplete
By Cristian Y S C
•May 9, 2024
The contents are well developed. Maybe other types of case studies should be presented to cover different topics.
By Satyender K M
•Apr 27, 2021
learned the concept very nicely by attempting the quizzes multiple times.
Thank You, IBM for creating this course.
By Eliza G
•Sep 30, 2020
a very structural sound and informative course which gives a beginner like me a chance to learn the subject well.
By Amit L
•Jan 23, 2020
Excellent course to understand the Data Science Methodology to be used for any new data science project to begin.
By Emmanuel B
•Aug 2, 2019
Really good course in terms of helping data scientist tell a story that gives meaningful insight to the business.
By Vigneshwari R
•Apr 30, 2019
It was an interesting course which helped me to understand the best practices to be a professional Data Scientist
By Charles O
•Apr 27, 2019
Data science methodology on coursera is well packed with lots information and easy to understand.
Great job y'all.
By Tiago P F
•Mar 3, 2019
Very clear and practical explanations of Data Science Methodology, with a very good example of the whole process.
By Diego C
•Mar 11, 2024
Excellent way to explain the methodology! Great understanding derived from it. Thank you, keep up the good work!
By Kunal J
•Oct 22, 2019
Really tells us about the Data science problem approach . Every aspiring data scientist should try this course .
By Andrei L
•Jun 23, 2019
I think it is very significant course that is helpful not only for data scientists, but also for any researcher.
By mohamed y
•Feb 27, 2021
this course was easy and strongly illustrates the data science process and define every process with case study