Chevron Left
Вернуться к Статистика для науки о геномных данных

Отзывы учащихся о курсе Статистика для науки о геномных данных от партнера Университет Джонса Хопкинса

4.1
Оценки: 174
33 рецензий

О курсе

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....

Лучшие рецензии

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

Фильтр по:

1–25 из 30 отзывов о курсе Статистика для науки о геномных данных

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 NAMRATA P

Apr 10, 2019

good

By Tushar K

Mar 25, 2019

Very good course and useful understanding statistical aspects of data.

By Dr. P R I

Mar 01, 2019

good

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 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.

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 Hemanoel P A

Jan 24, 2019

This is totally not for beginners..

By Hamzeh M T

Nov 08, 2018

Great place to start learning genomics in R

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 李仕廷

Jul 01, 2018

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

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 Thodoris S

May 23, 2018

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

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 Roman S

Jan 04, 2018

Really great and in-depth class! thank you

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 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.

By Apostolos Z

Oct 21, 2017

Excellent course! Thank you!

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 Alex Z

Aug 07, 2017

talk fast and informative! I enjoyed it a lot.

By 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.

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 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.

By Juan J S G

Mar 07, 2017

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

By Michael R D

Feb 12, 2017

Nice course. Ready to apply data.