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

4.3
stars
1,679 ratings

About the Course

This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University....

Top reviews

KR

Jul 16, 2018

A very good course for its length and the amount of time it requires. It improved my python skills and knowledge of Genomics. I'm more engaged in my pursuits than before taking the course.

AN

Jul 14, 2022

It was easy in the beginning but gets hard and changing at the end.

It was such an honor th have a course with Professor Salzburg.

I would recommend it to all bioinformatics lovers.

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151 - 175 of 331 Reviews for Python for Genomic Data Science

By M C

•

Apr 21, 2017

Great starter course

By Jeb H

•

Sep 30, 2020

Best course so far.

By IvyFields

•

Apr 21, 2020

very nice teachers

By Yuezhe L

•

Jan 22, 2017

it's very useful!

By Ben B

•

Jul 22, 2023

Good, thank you.

By Dr M R

•

Nov 28, 2021

excellent course

By Guillermo D A

•

Sep 11, 2021

Excelente Curso!

By Ray H A L

•

Nov 23, 2022

Great! learning

By W W

•

Sep 4, 2016

Just excellent!

By Chunyu Z

•

Feb 10, 2016

very good class

By Wilson G

•

Sep 15, 2022

Great course

By Sahan P

•

Jul 26, 2020

Great Content

By pasan m w

•

Dec 25, 2020

Good Course

By Dina A

•

Jun 27, 2022

very good

By Alejandra S

•

Jul 4, 2021

Excelente

By Albert C G

•

Jun 27, 2018

Well Done

By Timothy S

•

May 3, 2016

I like it

By Chandra S

•

Aug 7, 2021

By Sameer R

•

May 24, 2021

The final exam was too intensive for the level of content presented throughout the course. If one wishes to maintain a sufficient level of quality in instruction to handle the final exam without wasting large amounts of time, I strongly suggest additional resources be added in order to accomplish this task. Other than that, it was a nice, very basic introduction to see how Python can be used in genomic data science. It is a bit disappointing to be this far into the specialization and not be introduced to advanced, state of the art methods for genomic data science that are used in industry or research today.

By Onur S

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Feb 17, 2018

This is a quick introduction into Python for biological data. I would say there is much more to Python than what's included in this course, however the material was presented quite clearly. I had to increase the playing speed of the videos a bit, all the slow-talking was quite distracting after some time. The quiz questions were sometimes a bit tricky and I liked that. Final exam is much more difficult than the quiz questions and requires significant effort. To be honest it was a bit easy for me to pass, but that's because I've previously solved similar problems at rosalind.info.

By changqing z

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May 31, 2022

This course is kind of difficult. The content is very good though. It overviews all the important steps that are needed for performing the work, but in a very shallow way. If you want to get things done or trouble shoot, you'll need to do extensive research on your own. I have learned python before and I've been working in gene sequencing company for a few years, but there are still some steps, like using command line, installing Biopython, running files...that I need to learn from other resources.

By Yuntian G

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Jul 26, 2023

Very efficient introduction to python under biological context, focus on applications for biologists.

The only drawback is that there lack sample files/sequences to work with. When the instructor give an example (like processing a DNA sequence) I have to get the same DNA sequence by extracting the text from a lecture screenshot. There are also several videos about processing some files without providing a downloadable file for students to practice alongside watching video.

By Kasper T K

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Nov 21, 2017

Fairly good course for introducing basic programming skills for biological sequence analysis. However instructions for the assignments (weekly quizzes) should include some basic testing, where expected answers are given, so you can begin debugging before you answer the quiz, contrary to debug between doing quizzes. When you are getting the wrong answers it can be quite difficult to determine what went wrong, if you can't test your progress against a given example.

By Roy L

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May 17, 2018

The content of the course is quite good, but it would have been nice if they addressed more how to make code run efficiently in Python (e.g. which structures are fast and which should be avoided). Especially during the final exam the way you approach the questions can result in a running time from seconds to hours. As in practice the datasets you will work with tend to be quite large, I think this would be a valuable addition to the course.

By Mona W

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Feb 19, 2023

It's not very friendly and helpful for people unfamiliar with programming. All lectures show coding and concept using slides. It will be better if students get a chance to write programs along with the lectures or provide a coding template to follow along. I was still confused about which tool I should use at the end of the course.

I had some background in R, but, it still, took me a very long to pass the course.