Chevron Left
Back to Statistics for Genomic Data Science

Learner Reviews & Feedback for Statistics for Genomic Data Science by Johns Hopkins University

4.2
stars
353 ratings

About the Course

An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University....

Top reviews

ZM

Jun 27, 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!

CJ

Jul 15, 2019

It is really great that told me lots of basic statistical information that I didn't know.

Filter by:

26 - 50 of 62 Reviews for Statistics for Genomic Data Science

By Luz Y M R

May 23, 2016

I have really enjoyed the course and I have learnt different concepts relevant for my current study.

Yurany

By 李仕廷

Jun 30, 2018

really a good course for people who want to learn use R to dispose genomic data

By Juan J S G

Mar 7, 2017

La semana 3 puede hacerse dura, pero el curso es muy completo y recomendable.

By Manali R

Mar 4, 2020

Great course as a starting point for statistical genomics!

By Alex Z

Aug 6, 2017

talk fast and informative! I enjoyed it a lot.

By Chunyu Z

Feb 10, 2016

very helpful class. instructor very organized.

By Hamzeh M T

Nov 7, 2018

Great place to start learning genomics in R

By Renaud E

Jul 23, 2020

Difficult but definitively very valuable !

By Roman S

Jan 4, 2018

Really great and in-depth class! thank you

By Apostolos Z

Oct 21, 2017

Excellent course! Thank you!

By David G M

May 30, 2023

Challenging but worth it

By Maximo R

Mar 22, 2016

Great course!!!!

By Felix K

Jul 22, 2021

Great course

By Mingzhi L

Jun 2, 2021

Useful!

By yuan L

Sep 8, 2019

Thanks!

By Charles W

Jan 2, 2021

I thought this course covered a good set of relatively well-organized material.

I think some of the quiz questions (and optional analysis) was a little buggy in Week 1 (where I needed to use different versions of R for different questions), and I am not sure if that is because some time has passed since the course was first created. There were also issues for some of the questions in the other weeks, but I don’t remember being as frustrated when figuring out how to get an answer that was counted as correct (or, more specifically, not being able to run the intended code).

Additionally, I think this course will probably take more time to complete than listed in the syllabus. I support needing to take more time to learn the material, but I think the estimates can be kind of important when deciding if there is enough time to take the course (for somebody who already has a full time job).

There was also at least one section in Week1 that I thought was more of an opinion. For example, there are important and popular programs for genomic analysis that are *not* available through Bioconductor (including some mentioned in Week 4), and I don’t think they are less “trustworthy.” However, I agree that listing resources and explaining the differences is important.

I think I mentioned it in another course review, but I think the limitations to the methods are something to consider. So, I agree that p-hacking can be a problem, but I think telling people that they should only analyze their data once can also cause problems. I also agree with sharing a public log, even if the problems/bugs that are fixed are not emphasized as much in an official report/problem (as findings that should be given weight in the conclusions, if you found reason why they were wrong).

I noticed that there was a moderator responding to forum questions, so that was nice.

I imagine that I might participate a bit more, even though I have formally completed the course.

Thank you!

By Niko F

Mar 17, 2021

Nice overview over the different statistics for genomics studies. Very useful commentary for the scientific usefulness of each statistic and helpful literature suggestions. At times a bit unstructured and confusing regarding chapter titles and sequence.

By Osman M

Aug 30, 2023

It is a good course as an introduction. But you need some statistical background to grasp some of the lessons. One major issue with the course is that it is outdated; I hope they update this course with more new content.

By Ryan A H

Feb 11, 2017

Overall, a very good course. Not without its flaws (inconsistent video audio levels), but I have walked away knowing far more about Genomic Data Science than I expected to.

By Nitin S

Feb 19, 2019

sometimes termininology was used interchangeably, which can be confusing for a beginner but overall a good introduction to statistcs for genomic data analysis

By Saaket V

Feb 19, 2018

Enjoyed it. One of better courses I have taken in Coursera. A good introduction to using statistics in Bioconductor with genomics data.

By eman m a

Jul 1, 2020

theoretical parts need more explanation. But in general, It is a well-structured course. thanks for your efforts

By Maria J

Aug 8, 2020

Very helpful and i understood i should master statistics and do more research

By tawanda n

Jan 23, 2020

new material would be great as well as new datasets

By Pedro M

Mar 26, 2020

Pretty good but a little superficial and outdated.