Comentários e feedback de alunos de Logistic Regression in R for Public Health da instituição Imperial College London
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Melhores avaliações
RP
18 de dez de 2020
Very good specialisation on logistic regression, with depth info not only on how-to of the model creation itself, but interpreting and choosing between multiple ones. I fully recommend it.
RR
23 de dez de 2020
This is a wonderful course. Anyone who wants to model a binary classification model must go for this course. It covers everything in details with logic and humour.
51 — 64 de 64 Avaliações para o Logistic Regression in R for Public Health
por MAJEDA M
•17 de nov de 2021
very good
por Shakil A S
•17 de fev de 2021
Amazing!
por Sidney d S P B
•28 de jun de 2020
Perfect!
por Kim S J
•13 de jul de 2020
Good!!
por Hector P
•1 de out de 2020
I enjoyed this course, although I wish they will have more detailed examples. Some lectures are quite long. But in general the instructor is quite clear and the course is well designed. Now it is my time to practice.
por Vaishnavi N
•13 de jul de 2020
This is a great course though it was very challenging.It may take enough time for you to understand each concept clearly, but i think it is worth learning.
por Mohamed G M
•24 de ago de 2020
some parts were harder to understand and I thought it needs more examples. but generally a very nice course and a very nice instructor.
por Ahmed M Y O
•12 de set de 2019
would have helped if there were even a glance about logistic with multiple outcomes
por Shaukat A
•16 de set de 2020
Very good course
por Jean-Philippe M
•20 de jan de 2021
Great course!
por Debasish K
•3 de ago de 2020
Pros: (1) A great effort to give an understanding of fit, prediction and commands in R. (2) It covers important commands.
Cons: (1) The content was vague at times. Too much was left for the lecturer to tell and not enough visualizations provided in the video. Like what you do with data from the start of the EDA journey (There could have been a cheat sheet on the relation between the values (coefficients, p-values, etc).
Two areas of improvements: (1) Use more visualiations in the lecture. Like explaining the summary outout in R. Perhaps there were technical odds of doing it in the video and that got translated into Reading material. (2) The Reading Material is not sequenced well. So, consider 'residual deviation' and 'deviance residual'. What is the difference? I had to go to https://rpubs.com/fhernanb/deviance_glm to understand without any difficulty. As opposed to a lot of text in the Reading Materials, a notebook approach would be better. Attempt was made but it lacked the clarity of Rpubs. (3) The Practice Quiz was very easy while the multiple choice in the Final Quiz was baffling (since the Reading material was not adequate).
Thank you. Hope this helps.
por Rishi j
•3 de dez de 2019
Videos in the course were of no use
por Tommy K
•28 de fev de 2021
Its okay
por Kedeen O
•13 de jan de 2021
I had a problem with running the logistic regression in R since the missing observations that R gave me was not the same as given in this course. Therefore, due to missing observations in R not being the same as the missing values stated in these modules, I had a hard time answering some of the quiz, particularly Week 3. I requested for help but I did not get a response, I eventually solved the problem but going into Excel and cleaning up my data.
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