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Updating Arm Learning Paths and Tutorial Links (#19548)
- Current links to relevant Arm Learning paths are just URLs rather than clickable links. Changed this. - Added newer, relevant learning paths. - Added newly released ExecuTorch on Arm Jupyter lab series as a useful next step alongside the learning paths.
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docs/source/backends/arm-ethos-u/tutorials/ethos-u-getting-started.md

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## Takeaways
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In this tutorial you have learned how to use ExecuTorch to export a PyTorch model to an executable that can run on an embedded target, and then run that executable on simulated hardware.
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To learn more, check out these learning paths:
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https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-llama3/
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https://learn.arm.com/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/
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To learn more, check out the [ExecuTorch on Arm Practical Labs](https://github.com/arm-education/executorch_on_arm_labs) series. This series provides a structured entry-point to developing with ExecuTorch on Arm, across both CPU and Ethos-U NPU.
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For quick learning paths showcasing short tutorials:
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- [Run Llama3 on Raspberry Pi 5 with ExecuTorch](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-llama3/)
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- [Visualize Ethos-U NPU Performance on FVP](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/)
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- [Image Classification with ExecuTorch on NXP i.MX 93 (Ethos-U65)](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/observing-ethos-u-on-nxp/)
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- [Image Classification with ExecuTorch on Alif E8 DevKit (Ethos-U85)](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/alif-image-classification/)
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## FAQs
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