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Learner Reviews & Feedback for Introduction to Neurohacking In R by Johns Hopkins University

4.6
stars
281 ratings

About the Course

Neurohacking describes how to use the R programming language (https://cran.r-project.org/) and its associated package to perform manipulation, processing, and analysis of neuroimaging data. We focus on publicly-available structural magnetic resonance imaging (MRI). We discuss concepts such as inhomogeneity correction, image registration, and image visualization. By the end of this course, you will be able to: Read/write images of the brain in the NIfTI (Neuroimaging Informatics Technology Initiative) format Visualize and explore these images Perform inhomogeneity correction, brain extraction, and image registration (within a subject and to a template)....

Top reviews

BR

Feb 8, 2017

I like that this course goes through most necessary steps, my only suggest would be to have one additional week where you go through everything all together, and then do some simple group analysis.

SJ

May 7, 2019

Thank you for the wonderful course. Especially useful when the team explains every new line of code. As a current undergraduate and aspiring neuroscience researcher, this is tremendously helpful.

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1 - 25 of 49 Reviews for Introduction to Neurohacking In R

By Brandy R

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Feb 9, 2017

I like that this course goes through most necessary steps, my only suggest would be to have one additional week where you go through everything all together, and then do some simple group analysis.

By Ana-Maria N S

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Aug 9, 2016

This course offers a comprehensive description of all the steps required for the analysis of brain images. The notes are clear, concise, and contain a lot of helpful information about reading medical images, pre-processing them, and visualizing them. I'm a statistics researcher, and had very limited prior experience on this topic; but feel that this course has helped me tremendously to acquire the knowledge necessary to dive into research in this area, in a very short time. However, the benefits of taking this class go beyond this. Specifically, I was thrilled to be able to apply the techniques described here to read and visualize in R, medical images (MRI) concerning a patient-friend diagnosed with brain tumor, obtained directly from the doctor's office !!! And this, I thought, was amazing!

By jeremy s

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May 8, 2019

Thank you for the wonderful course. Especially useful when the team explains every new line of code. As a current undergraduate and aspiring neuroscience researcher, this is tremendously helpful.

By Sanket G

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Aug 29, 2020

The process of downloading packages on the virtual machine was very tiring. The documentation of it could have been provided more nicely. Like I was not aware about the 'sudo...'on LINUX.

By xiaodong c

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Feb 5, 2022

wish to have more programming practice

By Sreenivasulu U

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Dec 27, 2019

This course was very useful for me to kick start working with brains and NeuroImaging this course gave me a deep insight into types of brain data that is available for use and also how to read them. Previously I had a fear of where to kick start now after completing this course I got an idea of how to work with brain data and do Neurohacking ;p

By Dadarkforce

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Apr 14, 2018

Great course. Learned quite a lot from the course. Only problem was the difficulty at first with the software and libraries stubbornly refusing to get setup. But, after realizing there was a VM provided with all intended software installed, everything was smooth sailing from there.

By Lara P

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Jul 28, 2017

Very comprehensive step-by-step introduction to imaging analyses using R. Also includes helpful information on the nature of files and processes. I am not sure that I will do my imaging analyses using R but still found this to be a very useful introduction to the topic.

By Dan S

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Sep 26, 2019

Thank you to the team for setting up this course! I learned a lot about manipulation of imaging data within R, which is something I previously executed at the command line within FSL. These formats will provide more reproducible code within my publications.

By Anna N

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Jul 18, 2017

Perfect! Precise to the subject and provides a lot of hands-on details, which is, unfortunately, something that most other similar courses don't do. Absolutely loved it!

By Hanem E

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Dec 17, 2019

A very useful and informative course. An organized, well prepared, and focused course. Thanks to the fabulous team. I learned a lot of stuff related to neuroimaging.

By Freeman

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Apr 26, 2017

Wonderful course. I have mastered much about neurohacking using R programming, and learned about the preprocess step in neuroimaging analysis.

By Fernando M

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Sep 19, 2016

Very good as introduction to this area of implementation , It will be very interesting to create another course with more advanced topics.

By JM S

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Jan 19, 2017

It would have been better if there were practical exercises, nevertheless it was very comprehensive for basic procedures of fMRI analysis.

By Suhail K

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Jun 29, 2020

Very Informative. I suggest all people who are seeking to gain knowledge about image processing should definitely check this out.

By Syed M A

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Aug 20, 2019

it would be great if can create a specialization for this course going in more depth like making your own dti films etc.

By Ankit S

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Aug 26, 2017

I am really appreciate this course. Its good to have a structured course on these complex topics.

By christina J

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May 30, 2020

This course is very useful for the beginners to analyse the neruo-images. Thanks a lot

By Belfin R V

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Apr 8, 2020

Thanks for the course. It was a nice course with good explanation. I enjoyed learning.

By Lydia D

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Oct 8, 2019

A nice introduction to neurohacking in R. I would recommend this course for beginners.

By Spyridon S

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Sep 4, 2016

An excellent introduction to neuroimaging analysis! Tank you.

By Chandan V

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May 17, 2017

Great course....medical imaging techniques at its best :)

By Dinara Y

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Oct 13, 2020

An amazing introduction to neuroimaging in R! Thank you!

By Rajavarman K

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Aug 21, 2020

Nice Course.Wonderful material.Enjoyed learning it.