# Tag: Cortex-A

## Filter

**Categories**
- Automotive
- Embedded and Microcontrollers
- Laptops and Desktops
- Mobile, Graphics, and Gaming
- Servers and Cloud Computing

## Learning paths

- [Run an optimized vision-language model from the Arm AI Portal on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-portal-mobile-vision-language/)
- [Inspect model artifacts and runtime profiles with Google Model Explorer and Arm extensions](https://learn.arm.com/learning-paths/cross-platform/explore-model-artifacts-with-model-explorer/)
- [Deploy Unity Machine Learning Agents on Arm Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/using_unity_machine_learning_agents/)
- [Optimize image processing on Android using Halide](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_halide/)
- [Deploy IoT applications with AWS IoT Greengrass and Arm Virtual Hardware](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/avh_greengrass/)
- [Accelerate Generative AI workloads using KleidiAI](https://learn.arm.com/learning-paths/cross-platform/kleidiai-explainer/)
- [Learn SVE and SME programming with SIMD Loops](https://learn.arm.com/learning-paths/cross-platform/simd-loops/)
- [Porting architecture specific intrinsics](https://learn.arm.com/learning-paths/cross-platform/intrinsics/)
- [Run an Arm AI Portal depth estimation model on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-depth-anything-v2-on-android/)
- [Get started with Realm Management Extension (RME)](https://learn.arm.com/learning-paths/cross-platform/cca_rme/)
- [Get started with Microcontrollers](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/intro/)
- [Get started with Laptops and Desktops](https://learn.arm.com/learning-paths/laptops-and-desktops/intro/)
- [Deploy models with the Arm AI Portal](https://learn.arm.com/learning-paths/cross-platform/ai-portal-model-deployment/)
- [Run an Arm AI Portal image segmentation model on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-image-to-image-models-on-android/)
- [Profile llama.cpp performance with Arm Streamline and KleidiAI LLM kernels](https://learn.arm.com/learning-paths/servers-and-cloud-computing/llama_cpp_streamline/)
- [Optimize network interrupt handling on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/irq-tuning-guide/)
- [Convert SmolVLA to ExecuTorch for inference on Arm CPUs](https://learn.arm.com/learning-paths/laptops-and-desktops/smolvla-executorch-conversion/)
- [Deploy ML models to Arm edge devices using Edge Impulse and AWS IoT Greengrass](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/edge_impulse_greengrass/)
- [Optimize performance using Link-Time Optimization with GCC](https://learn.arm.com/learning-paths/servers-and-cloud-computing/gcc-lto/)
- [Run optimized object-detection models from the Arm AI Portal on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-portal-mobile-object-detection/)
- [Compare KleidiCV Gaussian blur performance across Neon, SVE2, and SME on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/explore-kleidicv-gaussian-blur-on-android/)
- [Port Code to Arm Scalable Vector Extension (SVE)](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve/)
- [Migrate applications between Arm platforms using Kiro Arm SoC Migration Power](https://learn.arm.com/learning-paths/servers-and-cloud-computing/arm-soc-migration-learning-path/)
- [Get ready for performance analysis with Sysreport](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sysreport/)
- [Deploy an AWS IoT Greengrass custom component to Arm devices and verify PAC/BTI support](https://learn.arm.com/learning-paths/cross-platform/aws-greengrass-pacbti-test/)
- [Build NVIDIA JetPack Yocto images for Jetson Orin NX, Orin Nano, and Thor platforms](https://learn.arm.com/learning-paths/cross-platform/nvidia-jetpack-yocto-build/)
- [Build a CCA Attestation Service on AWS with Veraison](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-veraison-aws/)
- [Access running containers using Supervisor, SSH, and Remote.It](https://learn.arm.com/learning-paths/servers-and-cloud-computing/supervisord/)
- [Distribute a ROS 2 robotic system across Arm devices with Zenoh](https://learn.arm.com/learning-paths/cross-platform/distributed-ros2-zenoh-lp2/)
- [Run optimized TinySD image generation from the Arm AI Portal on Arm-powered Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-portal-tinysd-android/)
- [Run optimized image classification models from the Arm AI Portal on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-portal-mobile-image-classification/)
- [Run Arm AI Portal text-generation models on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-text-to-text-models-on-android/)
- [Run optimized Whisper speech transcription models from the Arm AI Portal on Arm-powered Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-portal-audio-to-text/)
- [Tune Zenoh for ROS 2 traffic over wireless networks](https://learn.arm.com/learning-paths/cross-platform/tuning-zenoh-ros2-lp3/)
- [Run Confidential Containers with encrypted images using Arm CCA and Trustee](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-kata/)
- [Run an end-to-end attestation flow with Arm CCA and Trustee](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-trustee/)
- [Get started with CCA Attestation and Veraison](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-veraison/)
- [Explore secure device attach in Arm CCA Realms](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-device-attach/)
- [Export and quantize SmolVLA for ONNX Runtime on Arm](https://learn.arm.com/learning-paths/cross-platform/smolvla-onnx-conversion/)
- [Fine-tune SmolVLA for an SO-101 pick-and-place task on an NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/finetune-smolvla-lerobot/)
- [Profile Unity application performance on Android devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/profiling-unity-apps-on-android/)
- [Profile the Performance of AI and ML Mobile Applications on Arm](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/profiling-ml-on-arm/)
- [Optimize Unity applications on Android using Neon intrinsics](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/using-neon-intrinsics-to-optimize-unity-on-android/)
- [Build a Sentiment-Aware Voice Assistant with On-Device LLMs](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/voice-sentiment-analysis-with-llm/)
- [Accelerate multimodal Voice Assistant performance with KleidiAI and SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/voice-assistant/)
- [Generate audio with Stable Audio Open Small using ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-stable-audio-with-executorch/)
- [Generate audio with Stable Audio Open Small on LiteRT](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/run-stable-audio-open-small-with-lite-rt/)
- [Run Vision LLM inference on Android with KleidiAI and MNN](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/vision-llm-inference-on-android-with-kleidiai-and-mnn/)
- [Install and Use Arm integration packages for Unity](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/unity_packages/)
- [Install a Unity Game on a single board computer (Orange Pi 5)](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/unity_on_orange_pi/)
- [Profile ONNX model performance with SME2 using KleidiAI and ONNX Runtime](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/performance_onnxruntime_kleidiai_sme2/)
- [Explore Arm Memory Tagging Extension with an example C program](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/mte/)
- [Run LLM inference on Android with KleidiAI, MediaPipe, and XNNPACK](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/kleidiai-on-android-with-mediapipe-and-xnnpack/)
- [Benchmark a KleidiAI micro-kernel in ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/measure-kleidiai-kernel-performance-on-executorch/)
- [Accelerate LiteRT Models on Android with KleidiAI and SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/litert-sme/)
- [Profile Android game performance in Godot with Arm Performance Studio](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/godot_packages/)
- [Deploy optimized ML models with ONNX Runtime on Arm platforms](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/)
- [Enable Memory Tagging Extension on Google Pixel 8](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/mte_on_pixel8/)
- [Advance robotics reinforcement learning with Isaac Lab on DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_isaac_robotics2/)
- [Build Robot Simulation and Reinforcement Learning Workflows with Isaac Sim and Isaac Lab on DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_isaac_robotics/)
- [Query Arm GPU configuration information](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/libgpuinfo/)
- [Get started with Unity on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/get-started-with-unity-on-android/)
- [Debug with MTE on Google Pixel 8](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/debugging_with_mte_on_pixel8/)
- [Profile the Linux kernel with Arm Streamline](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/streamline-kernel-module/)
- [Get started with the Raspberry Pi 4](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi/)
- [Build embedded Linux applications on an Arm server](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-mxnet/)
- [Run Llama 3 on a Raspberry Pi 5 using ExecuTorch](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/rpi-llama3/)
- [Get started with Yocto Linux on Qemu](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/yocto_qemu/)
- [Visualize Ethos-U NPU performance with ExecuTorch on Arm FVPs](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/visualizing-ethos-u-performance/)
- [Build a Universal Single Board Computer Rack Mount System](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/universal-sbc-chassis/)
- [Migrating x86_64 workloads to aarch64](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/migration/)
- [Build a Privacy-First LLM Smart Home on Raspberry Pi 5](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/raspberry-pi-smart-home/)
- [Deploy multi-network device meshes using Device Connect server and NATS](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/device-connect-server/)
- [Use Linux on the NXP FRDM i.MX 93 board](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/linux-nxp-board/)
- [Prepare Docker image for Arm embedded development](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/docker/)
- [Learn about the impact of stack buffer overflows](https://learn.arm.com/learning-paths/servers-and-cloud-computing/exploiting-stack-buffer-overflow-aarch64/)
- [Debug Trusted Firmware-A and the Linux kernel on Arm FVP with Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/linux-on-fvp/)
- [Run a local LLM chatbot on a Raspberry Pi 5](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/llama-python-cpu/)
- [Introduction to TinyML on Arm using PyTorch and ExecuTorch](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/introduction-to-tinyml-on-arm/)
- [Get started with object detection using a Jetson Orin Nano](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/jetson_object_detection/)
- [Deploy ExecuTorch firmware on NXP FRDM i.MX 93 for Ethos-U65 acceleration](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/observing-ethos-u-on-nxp/)
- [Create a ChatGPT voice bot on a Raspberry Pi](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/raspberry_pi_chatgpt_bot/)
- [Add new debug targets to Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/new_debug_targets_armds/)
- [Sampling CPython with WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf_sampling_cpython/)
- [Get started with Windows Subsystem for Linux on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/wsl2/)
- [Get started with the Windows Performance Analyzer plugin for WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf_wpa_plugin/)
- [Develop desktop applications with Windows Forms on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_forms/)
- [Automate Windows on Arm virtual machine deployment with QEMU and KVM on Arm Linux](https://learn.arm.com/learning-paths/laptops-and-desktops/win11-vm-automation/)
- [Port the Win32 library to Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_win32_dll_porting/)
- [Measure application resource and power usage on Windows on Arm with FFmpeg and PowerShell](https://learn.arm.com/learning-paths/laptops-and-desktops/win-resource-ps1/)
- [Develop Windows applications with WinUI3 on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_winui3/)
- [Deploy GitHub Actions workflows using Windows Sandbox](https://learn.arm.com/learning-paths/laptops-and-desktops/win_sandbox_dot_net_cicd/)
- [Create OpenCV applications on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win-opencv/)
- [Analyze performance data with the Visual Studio extension for WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf-vs-extension/)
- [Optimize AArch64 binaries with LLVM BOLT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bolt/)
- [Develop desktop applications with Chromium Embedded Framework on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_cef/)
- [Build a Windows on Arm native application with .NET](https://learn.arm.com/learning-paths/laptops-and-desktops/win_net/)
- [Build .NET MAUI Applications on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_net_maui/)
- [Run Phi-3 on Windows on Arm using ONNX Runtime](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/)
- [Optimize Windows applications using Arm Performance Libraries](https://learn.arm.com/learning-paths/laptops-and-desktops/windows_armpl/)
- [Optimize C++ applications on Windows on Arm using profile-guided optimization](https://learn.arm.com/learning-paths/laptops-and-desktops/win_profile_guided_optimisation/)
- [Get started with WindowsPerf](https://learn.arm.com/learning-paths/laptops-and-desktops/windowsperf/)
- [Develop cross-platform applications with Xamarin Forms on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_xamarin_forms/)
- [Develop applications with Windows Presentation Foundation (WPF) on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_wpf/)
- [Build native Windows on Arm applications with Python](https://learn.arm.com/learning-paths/laptops-and-desktops/win_python/)
- [Benchmarking .NET 8 applications on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_net8/)
- [Optimize AArch64 code with LLVM link-time optimization and profile-guided optimization](https://learn.arm.com/learning-paths/servers-and-cloud-computing/pgo/)
- [Extend OpenClaw for a local-first AI assistant across Arm platforms](https://learn.arm.com/learning-paths/laptops-and-desktops/openclaw_continuum/)
- [Secure Realms during boot using Arm Confidential Compute Architecture BootSync](https://learn.arm.com/learning-paths/servers-and-cloud-computing/cca-bootsync/)
- [Accelerate Denoising, Background Blur and Low-Light Camera Effects with SME2](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-camera-pipelines/)
- [Sample Instructions with WindowsPerf and Arm SPE](https://learn.arm.com/learning-paths/cross-platform/windowsperf_sampling_cpython_spe/)
- [Build a Hands-Free Selfie Android Application with MediaPipe](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/build-android-selfie-app-using-mediapipe-multimodality/)
- [Profile an Android application with Arm Performance Studio](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ams/)
- [Get started with Scalable Vector Extension 2 on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_sve2/)
- [Detect faces with OpenCV on Android Devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_opencv_facedetection/)
- [Build an Android chat application with ONNX Runtime API](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/build-android-chat-app-using-onnxruntime/)
- [Build a customer support chatbot on Android with Llama and ExecuTorch](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/customer-support-chatbot-with-llama-and-executorch-on-arm-based-mobile-devices/)
- [Add an LLM to your Android app with Arm's AI Chat library](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android-ai-chat-lib/)
- [Create Computer Vision Applications with OpenCV on Android Devices](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_opencv_camera/)
- [Build and profile a simple WebGPU Android Application](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_webgpu_dawn/)
- [Build an Android chat app with Llama, KleidiAI, ExecuTorch, and XNNPACK](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/build-llama3-chat-android-app-using-executorch-and-xnnpack/)
- [Accelerate an OpenCV-based Android Application with KleidiCV](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/android_opencv_kleidicv/)
- [Optimize SIMD code with vectorization-friendly data layout](https://learn.arm.com/learning-paths/cross-platform/vectorization-friendly-data-layout/)
- [Build and deploy multi-node Zenoh systems on Raspberry Pi](https://learn.arm.com/learning-paths/cross-platform/zenoh-multinode-ros2/)
- [Use SIMD.info to port SIMD intrinsics across Arm architectures](https://learn.arm.com/learning-paths/cross-platform/simd-info-demo/)
- [Understand the `restrict` keyword in C99](https://learn.arm.com/learning-paths/cross-platform/restrict-keyword-c99/)
- [Learn about integer and floating-point conversions](https://learn.arm.com/learning-paths/cross-platform/integer-vs-floats/)
- [Install Arch Linux with the i3 window manager on a Pinebook Pro](https://learn.arm.com/learning-paths/laptops-and-desktops/pinebook-pro/)
- [Build an on-device AI fitness tutor app on Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/ai-plank-tutor/)
- [Memory latency for application software developers](https://learn.arm.com/learning-paths/cross-platform/memory-latency/)
- [Deploy an MCP Server on Raspberry Pi 5 for AI agent interaction using OpenAI SDK](https://learn.arm.com/learning-paths/cross-platform/mcp-ai-agent/)
- [Build an embedded application with Rust and debug with Arm Development Studio](https://learn.arm.com/learning-paths/cross-platform/rust_armds/)
- [Deploy containerized workloads to Arm-based Linux targets with Topo](https://learn.arm.com/learning-paths/cross-platform/deploy-containerized-workloads-with-topo/)
- [Develop a native C++ library on an Arm-based machine](https://learn.arm.com/learning-paths/cross-platform/matrix/)
- [Write SIMD code on Arm using Rust](https://learn.arm.com/learning-paths/cross-platform/simd-on-rust/)
- [Use LLVM Machine Code Analyzer to analyze assembly performance on Arm](https://learn.arm.com/learning-paths/cross-platform/mca-godbolt/)
- [Run custom software for simulation with Arm IP Explorer](https://learn.arm.com/learning-paths/cross-platform/ipexplorer/)
- [Profile ExecuTorch models with SME2 on Arm](https://learn.arm.com/learning-paths/cross-platform/sme-executorch-profiling/)
- [Optimize C and C++ code using compiler autovectorization techniques](https://learn.arm.com/learning-paths/cross-platform/loop-reflowing/)
- [Create and train a PyTorch model for digit classification using the MNIST dataset](https://learn.arm.com/learning-paths/cross-platform/pytorch-digit-classification-arch-training/)
- [Build a multimodal retail restocking assistant on Armv9 with MNN](https://learn.arm.com/learning-paths/cross-platform/multimodel_mnn_v9/)
- [Access remote devices with Remote.It](https://learn.arm.com/learning-paths/cross-platform/remoteit/)
- [Run and benchmark BitNet-2B inference on Arm CPUs with Litespark-Inference](https://learn.arm.com/learning-paths/cross-platform/litespark-inference/)
- [Use self-hosted Arm64-based runners in GitHub Actions for CI/CD](https://learn.arm.com/learning-paths/laptops-and-desktops/self_hosted_cicd_github/)
- [Use AWS Lambda for IoT applications running on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_lambda/)
- [Use Amazon DynamoDB for your IoT applications running on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_dynamodb/)
- [Run ASP.NET Core Web Server on Arm64](https://learn.arm.com/learning-paths/laptops-and-desktops/win_asp_net8/)
- [Use Arm64EC with Windows 11 on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_arm64ec/)
- [Unlock quantized LLM performance on Arm-based NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_llamacpp/)
- [Run AI models with Docker Model Runner](https://learn.arm.com/learning-paths/laptops-and-desktops/docker-models/)
- [Orchestrate a persistent local AI agent with Hermes on NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_persistent_agent/)
- [Fine-tune PyTorch models on DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/pytorch-finetuning-on-spark/)
- [Create Linux virtual machines with Hyper-V](https://learn.arm.com/learning-paths/laptops-and-desktops/hyper-v/)
- [Automate Windows on Arm builds with GitHub Arm-hosted runners](https://learn.arm.com/learning-paths/laptops-and-desktops/gh-arm-runners-win/)
- [Adding Memory Tagging to a Dynamic Memory Allocator](https://learn.arm.com/learning-paths/laptops-and-desktops/memory-tagged-dynamic-memory-allocator/)
- [Use Amazon S3 for your IoT applications running Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_s3/)
- [Port applications to Arm64 using Arm64EC](https://learn.arm.com/learning-paths/laptops-and-desktops/win_arm64ec_porting/)
- [Install Ubuntu on ChromeOS Crostini as an LXC container](https://learn.arm.com/learning-paths/laptops-and-desktops/chrome-os-lxc/)
- [Develop cross-platform desktop applications with Electron on Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/electron/)
- [Build and run a native Windows on Arm Qt application](https://learn.arm.com/learning-paths/laptops-and-desktops/win_arm_qt/)
- [Build a RAG pipeline on Arm-based NVIDIA DGX Spark](https://learn.arm.com/learning-paths/laptops-and-desktops/dgx_spark_rag/)
- [Integrate AWS Lambda with DynamoDB for IoT applications running Windows on Arm](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb/)
- [Create IoT applications with Windows on Arm and AWS IoT Core](https://learn.arm.com/learning-paths/laptops-and-desktops/win_aws_iot/)
- [Build and test KleidiCV on macOS](https://learn.arm.com/learning-paths/laptops-and-desktops/kleidicv-on-mac/)
- [Build a Windows on Arm native application with clang](https://learn.arm.com/learning-paths/laptops-and-desktops/llvm_putty/)
- [Run the AV1 and VP9 codecs on Arm Linux](https://learn.arm.com/learning-paths/servers-and-cloud-computing/codec1/)
- [Optimize Arm applications and shared libraries with BOLT](https://learn.arm.com/learning-paths/servers-and-cloud-computing/bolt-merge/)
- [Deploy a machine learning application to the Arm Ethos-U65 NPU on NXP FRDM i.MX 93 with Topo](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/deploy-ml-model-to-npu-with-topo/)
- [Create and deploy a custom Topo Project](https://learn.arm.com/learning-paths/cross-platform/create-your-own-topo-project/)
- [Run a local AI agent with Ollama to visualize CPU orchestration on Arm](https://learn.arm.com/learning-paths/cross-platform/ai-agent-cpu-orchestration/)
- [Create an Armv8-A embedded application](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/bare-metal/)
- [Deploy IoT applications with Balena Cloud and Arm Virtual Hardware](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/avh_balena/)
- [Device-to-Device communication with Device Connect](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/device-connect-d2d/)
- [Design an AXI-Lite peripheral to control GPIOs](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/advanced_soc/)
- [Deploy firmware on hybrid edge systems using containers](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/cloud-native-deployment-on-hybrid-edge-systems/)
- [Getting started with CMSIS-DSP using Python](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/cmsisdsp-dev-with-python/)
- [Get started with Arm Development Studio](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/armds/)
- [Build IoT Solutions in Azure for Arm Devices](https://learn.arm.com/learning-paths/embedded-and-microcontrollers/azure-iot/)
- [Use the Eigen Linear Algebra Library on Arm](https://learn.arm.com/learning-paths/cross-platform/eigen-linear-algebra-on-arm/)
- [Understand floating-point behavior across x86 and Arm architectures](https://learn.arm.com/learning-paths/cross-platform/floating-point-behavior/)
- [Run ERNIE-4.5 Mixture of Experts model on Armv9 with llama.cpp](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/)
- [Learn how to use Docker](https://learn.arm.com/learning-paths/cross-platform/docker/)
- [Learn about function multiversioning](https://learn.arm.com/learning-paths/cross-platform/function-multiversioning/)
- [Build an edge AI Reachy Mini app with Raspberry Pi, MediaPipe, and MuJoCo](https://learn.arm.com/learning-paths/cross-platform/build-a-reachy-robot-app-on-pi/)
- [Boost C++ performance by optimizing loops with boundary information](https://learn.arm.com/learning-paths/cross-platform/cpp-loop-size-context/)
- [Write Neon intrinsics using GitHub Copilot to improve Adler32 performance](https://learn.arm.com/learning-paths/cross-platform/adler32/)
- [Write a Dynamic Memory Allocator](https://learn.arm.com/learning-paths/cross-platform/dynamic-memory-allocator/)
- [Automate MCP server testing using Pytest and Testcontainers](https://learn.arm.com/learning-paths/cross-platform/automate-mcp-with-testcontainers/)
- [Debug Arm Zena CSS Reference Software Stack with Arm Development Studio](https://learn.arm.com/learning-paths/automotive/zenacssdebug/)
- [Run Process watch on your Arm machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/processwatch/)
- [Get started with Arm hardware](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/intro/)