Comentários e feedback de alunos de Data Science Methodology da instituição IBM
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Melhores avaliações
This is a proper course which will make you to understand each and every stage of Data science methodology. Lectures are well enough to make you think as a data scientist. Thank you fr this course :)
Very interesting course. It shed a light on what the structured approach really is. It's worth to pause for a moment with every step of the methodology and think how to apply it in real life. Thanks!
1701 — 1725 de 2,016 Avaliações para o Data Science Methodology
por Prabhandini V
•Nice course
por Stephane B
•Nice course
por Jairo S B
•Very clear
por Abdulwasiu B
•Very good,
por JORGE D
•excelent!
por David L
•Thanks!!!
por Abdelhamid G
•very good
por Koyya S
•Thnakyou.
por ShanQiu
•Not bad~
por Amarzaya
•liked
por Osuolale E
•Great
por Raja M N
•good
por Muhammad S A
•good
por Shone G
•good
por Pagadala G s
•Good
por G V
•good
por Satishkumar M
•G
o
o
d
por Akhil K
•Good
por Savita M
•4.5
por Shruti R
•NA
por Adil S
•AS
por Néstor R V M
•:)
por Daniel L A
•-
por Andrei P
•The information was somewhat confusing at times and it was kinda hard to follow the lectures even though the information provided was quite basic nad not too complex. I guess the problem with this course is the way the information presented and the overall flow of the presentation.
Also the labs, they confused me even more because we get presented with some amount of code which was not covered before. You are supposed to be able to complete this course without any coding, but you get all this unnecessary code, which doesn't even matter in the end but adds to the confusion and makes the lab harder to follow. I think it would be better to get rid of the code, or to include these labs after the python course, so the students can easily follow what's actually going on in the labs.
As i figured from the discussion section there is a number of students that were a bit confused about what actually should be in the final assignment (myself included). I had to rewatch all of the videos and revisit all of the labs just to get vague understanding of what needs to be done.
I am still unsure if what i wrote in the final assignment was even 100% correct (even though i got the top score), simply because these assignments are being judged by peers, not mentors.
por Francisco M
•The course "data science methodology" provides a reasonable good overview of the main stages of a data science project based on a methodology similar to CRISP-DM methodology. Explanations are supported by two main examples: one related to "reducing risk readmission of patients in a hospital" and the other related to a study of "food recipes". In addition, some Jupyter Notebooks have been developed to make the course more practical. In general, I believe three weeks is not sufficient to cover all the phases of a data science project with enough detail. I think the video recordings do not provide clear and sufficient explanations of the different phases of a data science project. I also believe the course should provide further details, examples and Jupyter Notebooks to better address relevant issues in each of the phases of a project. I would add more "optional content" for students interested of additional details and examples. The final assignment seems not to be sufficient to prove that a student has understood the material. I think this course might benefit if students are already familiar with programming languages such as Python and query languages such as SQL (in other words, please consider adding these prerequisites for the course).
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