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Statistics for Genomic Data Science に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による Statistics for Genomic Data Science の受講者のレビューおよびフィードバック



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....



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!


Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.


Statistics for Genomic Data Science: 26 - 50 / 55 レビュー

by Renaud E


Difficult but definitively very valuable !

by Roman S


Really great and in-depth class! thank you

by Apostolos Z


Excellent course! Thank you!

by Maximo R


Great course!!!!

by Felix K


Great course

by Mingzhi L



by YuanL



by Charles W


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


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 Ryan A H


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


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


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


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

by Maria J


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

by tawanda n


new material would be great as well as new datasets

by Pedro M


Pretty good but a little superficial and outdated.

by Michael R D


Nice course. Ready to apply data.

by Ariful l


good for learning




by Dr. P R I



by Mihaela M


I liked how energetic the lecturer was. He clearly has a reasonable amount of experience and some of the tips he gave about doing statistics in the context of genomic studies were useful! I liked how the professor recommended some extra reading at the end of every topic. I also really liked the fact that he recommended some extra courses to be taken.

But despite that, the course itself was a bit too short - the topics introduced just scratched the surface. This made sitting through the R tutorials particularly tedious - how would one get the use of R tools to do the tasks, if they haven't understood the theory properly? I know it's supposed to be an intro course, but still in its current state it can be a bit confusing. I would suggest making it somewhat longer, so that the intro to each topic could be done a bit more in depth - maybe focusing a bit more on the theory, so that the students could get an intuition for the methods, rather than just doing R commands which for them mean nothing if the theory is still very blurry.



First, I really appreciate the enthusiasm of the instructor. And the overall topics introduced in the course cover a large amount of current genomic research. But there is still a lot of space for improvement. The course itself is not suitable for beginners, since it requires proficient R skills and some knowledge in statistics. The ways of illustration on many definitions are unprofessional and shallow, so it sounds confusing at least for me, who majored in public health and has some experience in this field. And the course is overall short, but the instructor tried to introduce as much as knowledge possible, which makes every point somewhat unclear. By the way, the descriptions of several exercises in the quizzes really make people confused.

by Catherine J


Because of short time frame for course, it couldn't present topics in sufficient depth to to practically applied. Well presented for an overview of statistical terminology.

by Xue S


This course covers a lot of useful information. However, it was very fast-paced and some of the concepts were not very clearly explained.

by Thodoris S


too much overlap with Jeff's course in introduction to genomic data science