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36	36	{{html}}
37	37	<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/ej03_r_-Rno" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
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	39	+=== [[Using the SpiNNaker neuromorphic compute system interactively>>https://www.youtube.com/watch?v=xtsaH40MrLQ||rel=" noopener noreferrer" target="_blank"]] ===
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	41	+**Level**: beginner(%%) **Type**: video tutorial
	42	+
	43	+This tutorial showcases how to run a version of a solution, how to allocate the SpiNNaker board and finally how to use the Neural Robotics Environment.
	44	+{{html}}
	45	+<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/xtsaH40MrLQ" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
	46	+{{/html}}
	47	+=== [[Neuromorphic Computing in EBRAINS (brief introduction to SpiNNaker and BrainScaleS)>>https://www.youtube.com/watch?v=zW1UfIccMtY||rel=" noopener noreferrer" target="_blank"]] ===
	48	+
	49	+**Level**: beginner(%%) **Type**: video presentation
	50	+
	51	+Steve Furber giving a brief overview of the neuromorphic compute systems at Heidelberg. Touching upon what is neuromorphic computing and how we can use it.
	52	+{{html}}
	53	+<iframe width="560" height="315" src="https://www.youtube-nocookie.com/embed/zW1UfIccMtY" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
	54	+{{/html}}
	55	+=== [[Accessing SpiNNaker>>https://flagship.kip.uni-heidelberg.de/jss/HBPm?mI=242&publicVideoID=9260||rel=" noopener noreferrer" target="_blank"]] ===
	56	+
	57	+**Level**: beginner(%%) **Type**: video tutorial
	58	+
	59	+This tutorial teaches you how to access SpiNNaker, specifically through Jupyter. It guides you through the SpiNNaker interface and its properties. The lecturer briefly touches on Spiking Neural Networks and what can be simulated with SpiNNaker. The tutorial further explains PyNN, how it relates to SpiNNaker and what the most useful parts of PyNN are.
	60	+