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Computational Training Resources
The Dynamic Brain Circuits Cluster hosts an introductory training course for matlab, and hosts online training courses for some other programing languages. For more into write us at firstname.lastname@example.org
For Fall 2018, The Matlab training sessions will be held every Friday from 2-3 PM in the NINC computer lab in the Brain Research Centre on First Floor of the UBC Hospital, Koerner Pavilion. Matlab Drop in help will also be available every Friday from 4-5 PM at the same location, and at 5 PM we will host our weekly Databinge Seminar Series on technology and techniques of interest to neuroscience researchers.
The UBC Brain Circuits Cluster onboarding portfolio is intended to introduce new cluster members and neuroscience graduate students to tools and resources that they may need as they begin their research at UBC. The portfolio is designed as a quick start guide and is therefore recommended as a reference for unfamiliar things that new members may encounter or new skills they may need to acquire.
Most of what is presented is central to neuroscience research and the portfolio encourages the use of free online resources that are catered directly to the needs of neuroscientists.
Major topics include Introduction to Coding, MATLAB, Python, Jupyter, statistics, data management, and image anaylsis.
Basic Programming Principles
A solid understanding of basic programming principles is an essential way to start before approaching any language. If you have very limited or no prior programming experience, we recommend reading this excellent introduction article here.
If you're interested in a more in depth introduction to programming concepts, there is an excellent FREE online course offered by pluralsight here.
Hacker.io reached out to us to suggest their website as a resource for programming classes. The website is impressively comprehensive as a compendium of classes and courses for MANY different subjects. If you're looking for something specific, this is a good place to search. Be aware that many of the courses are NOT free however, but its still definitely worth a look. Check out more here.
Where to get Matlab for UBC students
Information on downloading and installing Matlab under the UBC site license is available here.
Online matlab Training Resources
Approved Online training resources for Matlab we have reviewed:
If you have a Mathworks account, the Matlab Onramp Series is a great beginning introduction: Matlab Onramp
Matlab Training COurse:
Classes are currently being held on Fridays from 2-3 PM.
Drop-in Matlab help sessions are Fridays from 3-4PM.
For more information please write: email@example.com
Files and code for the matlab course can be found here
Where to get Python
Python is freely available software and can be downloaded from multiple sources. We recommend the following sources:
Python.org The official Python site, has the latest updates. This is the most basic implementation of Python.
Anaconda Anaconda offers a Python IDE with integrated packages for Data science and is a more robust and well rounded ready to use implementation. This version may be both easier to use and more complex for an early user.
In person Drop-In python support is available on Fridays from 3-4 PM in the NINC Computer Lab (room F130, First Floor Koerner Pavilion, just inside the door to the Brain Research Center).
Online Python Training Resources
Python.org has a great deal of resources from beginner's guides to coding in python to advanced user suggestions and a comprehensive guide to keywords and functions.
For a basic introduction to Python syntax and programming, you can find the Allen Brain Institute's Python Bootcamp code here. Note, the code should ideally be run in a Jupyter Notepad, more info on how to set up Jupyter is here.
Where to Get R
R is freely available Software, but we recommend downloading the open source edition Rstudio package here
Rstudio offers a full IDE (programming environment) for R and many useful packages to make the experience of working with R easier.
Tidyverse: We also recommend looking into the Tidyverse packages. Tidyverse is a collection of well thought out packages to encourage and accomplish best practices for data management and analysis for working in R. Also, the Tidyverse website has a link to the online book R for Data Science.
Online R Training Resources
R for Data Sciences mentioned above is a good introduction to working with R for analysis purposes, but also a good introduction to a proper data analysis workflow in general.
If you would like to suggest any online resources, we're always open to recommendations on the best online training courses. What worked for you? What has not worked for you? Let us know at firstname.lastname@example.org