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Volver a python para ciencia de los datos genómica

Opiniones y comentarios de aprendices correspondientes a python para ciencia de los datos genómica por parte de Universidad Johns Hopkins

1,544 calificaciones

Acerca del Curso

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....

Principales reseñas


16 de jul. de 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.


14 de jul. de 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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126 - 150 de 300 revisiones para python para ciencia de los datos genómica

por Rafał W

22 de mar. de 2019

Great Python refreshment course!

por Juan J S G

7 de mar. de 2017

Muy buena introducción a Python

por Olushola ( A

14 de oct. de 2017

Challenging but interesting!

por Andrew S

10 de sep. de 2022

We need Biopython course!

por YUE W

14 de may. de 2020

It is a very good course

por Phuong

3 de jul. de 2020

It's a great course!

por M C

21 de abr. de 2017

Great starter course

por Jeb H

30 de sep. de 2020

Best course so far.

por IvyFields

21 de abr. de 2020

very nice teachers

por Yuezhe L

22 de ene. de 2017

it's very useful!

por Dr M R

28 de nov. de 2021

excellent course

por Guillermo D A

11 de sep. de 2021

Excelente Curso!

por Ray H A L

23 de nov. de 2022

Great! learning

por Jingwei W

4 de sep. de 2016

Just excellent!

por Chunyu Z

10 de feb. de 2016

very good class

por Wilson G

15 de sep. de 2022

Great course

por PSD P

26 de jul. de 2020

Great Content

por pasan m w

25 de dic. de 2020

Good Course

por Dina A

27 de jun. de 2022

very good

por Alejandra S

4 de jul. de 2021


por Albert C G

27 de jun. de 2018

Well Done

por Timothy S

3 de may. de 2016

I like it

por Chandra S

7 de ago. de 2021

por Дубів О В

11 de nov. de 2022

Pros: in general - pretty valuable course

Cons: Python-related material can be extended; I'm sure the lady on videos is a highly skilled professional, but she seems not comfortable on a video and probably needs more engagement (we know how to read from slides); some tests were WRONG and I reported it

Exam: the worst part and almost vanished my desire to proceed with the course:

1) it's way too complex compared to the material given in lectures - I have professional experience in programming (PHP, MySQL, JS) but this Python exam took me about 6-8 hours to complete. It's not only because of Python I haven't got experience with - it's  also about other stuff I should know before submitting answers. I can't even imagine how students without programming skills can fulfill this exam sucessfully. It's like they teach you 2+2, and on exam they require to compute integrals....

2) exam questions (especially 3rd task) are vague. Samples given are very basic and don't show all the variety of edge cases and how to deal with them (i.e. nested ORF, what to do if we see one more Opened Codon etc) - it took most of exam's time to find some external learning resources and to know more theory. I used this resource also as a benchmark to know if what I get is correct: and it saved me.

3) PLEASE add at least couple of correct answers for sample data (dna.example.fasta file) for students to test their data against something before going on exam. Also add some more description and proper sample cases about codones: i.e. how to trean multiple ORF sequences if inside are some open or closed codons - how to determine the longest etc.

por Sameer R

24 de may. de 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.