A couple of years ago I completed the Coursera course Programming for Everybody (Getting Started with Python) with Charles Severance. I found it really well paced and well taught. He's a very personable tutor, and has also written a free book Python for Everybody, available as a PDF.

I found the Coursera course on R Programming with Roger Peng to be more difficult to follow, but I'm not sure whether that was down to the teaching style or the language itself. For R, I'd definitely recommend the best place to get started is swirl - Learn R, in R!

Happy coding

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Hello Claire, 

Engineer at Wild Me here. We would love to start a conversation about a Wildbook for rhinos. 

Lets talk about citizen science and computer vision for identification possibilities. I'm curious about your current data set and the identification tools you are using as a starting point. I'm happy to talk here, or you can email our team at [email protected].

Hi Claire,

At the BearID Project, we are working on a similar problem for brown bears. We are currently using machine learning methods developed for human facial recognition (like Google FaceNet). We got some ok initial results, but now we are running up against small data issues. The method for human faces were trained with millions of images of hundreds of thousandes on individuals. We have a few thousand images of about a hundred individuals. We plan to investigate other methods in the future.

It will be great to keep in touch to see what methods you will be using.

Ed

Hello Ollie,

SODA is a recently launched suite. It is in the development phase. We have with us call libraries with multiple (40+) calls for 10- 12 species of birds. A research scholar is on the job for classifying at the species level.

Our interest is equally on separating the different sonic components (as stated in https://www.wildlabs.net/community/thread/666). It is different from the link shared in my previous reply. This is where I see the confluence of objectives.

As a TEAM, I believe, we can address the individual objectives faster.

regards

jaishanker

Hi Ollie, 

Great article, thank you!  I mostly work with responsible AI in other contexts, at Doteveryone.org.uk and the Trust & Technology Initiative at the University of Cambridge, so don't have much to offer here, although I am very interested in the topic.  I appreciate your point that many of the consumer data issues highlighted in the 'popular' responsible AI discourse aren't relevant to conservation (some of us have been gathering 'responsible tech' / 'ethical tech' resources in a shared doc, and there's essentially nothing there for conservation specifically - https://docs.google.com/document/d/1SN6hYeKe3eRK6x9D0Sr7GpCA4nirpyo3u68xG1A6NDs/edit ). However there might be some links with humanitarian data practices, which are touched on by the Responsible Data folks at https://responsibledata.io and https://www.fabriders.net/data-literacy-consortium/ or in this recent article https://asecondmouse.wordpress.com/2019/02/20/instability-forecasting-models-seven-ethical-considerations/

Best, 

Laura