Opiniones y comentarios de aprendices correspondientes a Statistics for Genomic Data Science por parte de Universidad Johns Hopkins
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Principales revisiones
ZM
Jun 28, 2018
The professor is really enthusiasm, so I was really impreesed by him. And his teaching is brief, and I can learn key points through the lectures. Great course!
LR
May 23, 2016
I have really enjoyed the course and I have learnt different concepts relevant for my current study.\n\nYurany
26 - 35 de 35 revisiones para Statistics for Genomic Data Science
por Dr. R
•Mar 01, 2019
good
por Stefanie M
•Feb 25, 2019
In the course, easy concepts are well explained, but the more complex topics are very tricky to understand. However, I appreciated the enthusiasm of the teacher a lot
por John M
•May 25, 2017
Covers a large amount of material in a short time.
You will learn a lot but you will have to spend a lot of time researching and experimenting.
por sandeep s
•Dec 20, 2016
The course was tough and was explained in a very fast way assuming that the student knows prior statistics.
por Thodoris S
•May 23, 2018
too much overlap with Jeff's course in introduction to genomic data science
por Hemanoel P A
•Jan 24, 2019
This is totally not for beginners..
por Gonzalo C S
•Apr 04, 2017
Bad or superficial explanations. The instructor speaks very fast and you need to continually stop the video to keep the pace. Some interesting commands and are shown, but the instructor seems to be tired of explaining them and defers explanations to lots of links at the end of each video.
por David B
•Feb 24, 2019
Theory part, remaining that it has to be done in pills, could be done a lot better. R part is done better, but the principal issue is that you have not a clear connection with theory.
por Matt C
•Jun 27, 2017
For some reason, this was a really tough course, it blew my socks off. I did not get the explanations they just did not sink in.
por Andrew M
•Oct 29, 2017
This course is the shotgun approach to this topic. There's way too much material covered so shallowly that the instructor may as well not have bothered. While it is true that the course is heavily annotated with web links and references, IMNSHO, this is a cop-out. This course could improve dramatically by extending it a couple of weeks and covering some of the material in greater depth. I think the instructor also also buried his lede by deferring the discussion of predictive statistics and an overview various experimental processes/software until week 4. Both of these topics deserve better treatment front and center in week 1.
