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.

Author: matt-cossins

docs/source/backends/arm-ethos-u/tutorials/ethos-u-getting-started.md

@@ -196,10 +196,15 @@ The example application is by default built with an input of ones, so the expect
 ## Takeaways
 
 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.
-To learn more, check out these learning paths:
 
-https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-llama3/
-https://learn.arm.com/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/
+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.
+
+For quick learning paths showcasing short tutorials:
+
+- [Run Llama3 on Raspberry Pi 5 with ExecuTorch](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-llama3/)
+- [Visualize Ethos-U NPU Performance on FVP](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/)
+- [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/)
+- [Image Classification with ExecuTorch on Alif E8 DevKit (Ethos-U85)](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/alif-image-classification/)
 
 ## FAQs