Back to Statistics for Genomic Data Science

4.2

stars

228 ratings

•

41 reviews

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....

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!

May 23, 2016

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

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By Paul S

•Jan 03, 2018

The worst executed course I have taken in 36 years of post-graduate education.

1 The instructor speaks so fast it is difficult even for a native English speaker like myself to understand.

2. This course is only suitable as a review for people who are experts in the field already. Even if you know how to use Bioconductor and are familiar with programming in R, if you don't know the tools being used already the instruction in the course will not give enough information to be able to do the quizzes without a great deal of difficulty.

3. The examples presented are thrown out in a cursory fashion without enough detail about how the data is being set up or manipulated. Matrices are transformed and recombined with little explanation about why things are being done.

4. Although generalizing from material presented to new applications is a valid instructional approach, the instruction does not give the student enough information to do this and the instructor expects students to be able to figure out new algorithms from vague public domain documentation.

5. Although the instructor makes an impassioned plea for carefully thought out statistical test design, proper documentation of work flow, and appropriate use of p-values, he does not describe the interpretation of statistical tools presented. For example, tools for calculating thousands of principle components in seconds is given, but beyond showing clusters of dots on a graph may indicate a genetic cluster does not explain what the individual points in the PCA mean.

In summary, the tools presented are very powerful but are not well described. Extensive revision to the course is needed.

By Ian P

•Aug 30, 2018

I did my best to work through module 1, but encountered one problem after another with installing the various required R packages, due to version issues. From the absence of recent discussion posts it seems that this is not really a current, viable course. From what I have seen of the course, I get the impression that even if package installation went smoothly, the course is more about R than statistics or genomics - which is not what I joined for.

By Hylke C D

•Sep 25, 2019

Much of the code is broken because it is outdated. In the specialisation you learn to use Python, and here all of a sudden they switch to R. Some familiarity with R is assumed in this course. A lot of the functions and packages that are used are not discussed at all. By far the worst course I have taken on coursera so far.

By 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

By 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.

By sandeep s

•Dec 20, 2016

The course was tough and was explained in a very fast way assuming that the student knows prior statistics.

By ELISA W

•Jul 23, 2018

I think this is one of the best courses in this specialization. I found it the most helpful in building together what should be learned in genomic data science. I wish 1) this course was earlier in the specialization, 2) there was additional building from this course to build together the workflow from beginning to end, and 3) reduction or removal of some of the other courses (or other courses taught together with this one).

By Zhen M

•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!

By Gregorio A A P

•Aug 26, 2017

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

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 Chuan J

•Jul 16, 2019

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

By 李仕廷

•Jul 01, 2018

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

By Juan J S G

•Mar 07, 2017

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

By Tushar K

•Mar 25, 2019

Very good course and useful understanding statistical aspects of data.

By Manali R

•Mar 04, 2020

Great course as a starting point for statistical genomics!

By Alex Z

•Aug 07, 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 08, 2018

Great place to start learning genomics in R

By Roman S

•Jan 04, 2018

Really great and in-depth class! thank you

By Apostolos Z

•Oct 21, 2017

Excellent course! Thank you!

By Maximo R

•Mar 22, 2016

Great course!!!!

By YuanL

•Sep 08, 2019

Thanks!

By Ryan A H

•Feb 12, 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.

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