TECH VEDA

LSE / eLinux Fast-Track / Mastery track starts 25 Jun 2026 — enrolling now. See the Fast-Track
HomeTraining ProgramsEmbedded Linux on edge-AI platforms
Hands-on Enrolling now

Build a custom Linux distro and ship it on real edge-AI hardware — boot to deployed device

Embedded Linux on edge-AI platforms

Design, build and ship production Linux for modern embedded and edge-AI devices — from the boot process, kernel and root filesystem to custom distributions, over-the-air updates, on-device AI inference and a hardened, field-ready system.

🧱 Build with Yocto & BitBake
🔧 Board bring-up & BSPs
🚀 Ship on real edge-AI boards
Enroll now ★★★★★ Rated by 10,000+ engineers trained since 2003

OverviewAbout this program

This program equips participants with the essential skills to design, build and customise Linux for modern embedded and edge-AI devices. Starting with the embedded Linux ecosystem, you learn how Linux fits onto standard and custom hardware, the role of the bootloader, kernel and root filesystem, and how these components come together to power a real product.

A major focus is industry-standard custom Linux builds — configuring the kernel, selecting packages, creating board support packages (BSPs) and integrating applications into a deployable production image — before extending into field operations, on-device AI and security.

From there the program goes all the way to the field: building on real single-board and multicore hardware, deploying robust over-the-air updates with safe rollback, running on-device AI inference accelerated by dedicated hardware, and hardening the system end-to-end — secure boot, runtime protection and release-time compliance. The methodology is learn-by-doing: every concept is built, deployed and validated on real targets.

OutcomesWhat you'll be able to do

  • Understand the architecture of embedded Linux — bootloader, kernel, device tree and root filesystem.
  • Perform a complete board bring-up — cross-compilation, kernel configuration and deploying Linux to custom hardware.
  • Customise device trees and integrate hardware-specific drivers.
  • Work with peripheral interfaces — I²C, SPI, UART — and their role in embedded platforms.
  • Master the Yocto Project build system — layers, recipes, images and package management.
  • Build and customise Board Support Packages (BSPs) for target hardware.
  • Optimise Linux for footprint, performance and security in embedded deployment.
  • Build and ship over-the-air (OTA) updates with A/B partitions, signing and rollback.
  • Run and accelerate on-device AI inference on embedded Linux, including hardware-accelerator offload.
  • Secure embedded devices end-to-end — verified boot, runtime hardening, and CVE / SBOM release compliance.
  • Debug, extend and maintain embedded Linux systems for real-world products.

CurriculumEmbedded Linux foundations, the full Yocto stack, edge-AI deployment, OTA & security

Short conceptual sessions paired with immediate labs on real boards.

01Embedded Linux System
  • Introduction to embedded Linux
  • Key components
  • Bootrom & bootloader
  • Application binaries & rootfs
  • Init package
  • Build steps
02Build Systems
  • Build practices
  • The need for a build system
  • How build systems are structured
  • Popular build systems
03Buildroot
  • Introduction to the Buildroot project
  • Structure of Buildroot & build trees
  • Toolchain configuration
  • Kernel configuration
  • Rootfs configuration
04Yocto — Introduction
  • Yocto Project, OpenEmbedded-Core, Poky
  • BitBake
  • Setting up the host system
  • Installing Poky
05Poky
  • Poky repository
  • Preparing the build machine
  • bblayers.conf & local.conf
  • Image recipe
  • Generating an image for the emulator (QEMU)
06BitBake
  • The build system & metadata
  • Recipes, classes, configuration files
  • Types of layers (BSP, distro, software)
  • BitBake internals & tasks
07Layers
  • Creating a layer
  • File structure & directories
  • layer.conf variables
  • bitbake-layers & yocto-check-layer tools
08Recipes
  • Recipes vs packages
  • Recipe structure & key variables
  • Inheriting classes & implementing tasks
  • Recipe processing walk-through
09Advanced Recipes
  • Variable assignment syntax, overrides & flags
  • Append files & PACKAGECONFIG
  • Include & require directives
  • Versioning, priority & debugging
  • devshell, oe-pkgdata-util & other tools
10Images
  • Creating image recipes & package groups
  • Image features, users, groups & permissions
  • Post-install scripts & image formats
  • Distro configuration & features
  • Enabling package management
11BSP — Board Support Packages
  • Creating a BSP layer
  • Machine configuration & common variables
  • U-Boot & kernel variables, machine features
  • Bootloader, kernel & kernel-module recipes
  • Patches, kernel configuration & advanced metadata
12SDK
  • Toolchain, sysroot, scripts & tools
  • Generating SDKs · meta-toolchain
  • populate_sdk & populate_sdk_ext
  • Installing & using SDKs
  • Extensible SDK (eSDK) & devtool
13Production Images
  • Read-only root filesystems
  • Automated image testing
  • Reproducible builds
  • Package feeds & runtime package management
  • Release engineering workflow
14Hardware Platform — Raspberry Pi
  • Working with vendor BSP layers
  • Building & flashing hardware images
  • Serial console & first boot
  • Device tree overlays on real hardware
  • Peripheral interfaces — GPIO, I²C, SPI, UART
  • WiFi, Bluetooth & camera integration
  • Building a custom Raspberry Pi BSP
15Hardware Platform — TI Multicore SoC
  • Working with complex SoC BSPs
  • Multi-stage boot architecture
  • Multi-domain device trees
  • Peripherals — GPIO, PWM, CAN bus
  • Co-processors & firmware loading
  • Building a custom BSP for a multicore SoC
16OTA — Update Architecture
  • Why OTA — field updates at scale
  • Update strategies & framework comparison
  • A/B partition schemes
  • Bootloader integration & slot switching
17OTA in Practice
  • Update client integration
  • Update bundle creation & signing
  • Deployment server & fleet update management
  • Delta updates
  • Rollback, boot counting & health checks
18Edge-AI Foundations
  • The edge-AI software stack
  • Inference frameworks & runtimes landscape
  • Models, delegates & quantization
  • Cloud vs edge inference trade-offs
19AI Inference on Embedded Linux
  • Integrating an inference framework into Yocto images
  • Building inference applications
  • CPU-optimised inference on ARM
  • Camera capture pipelines for AI
20Hardware-Accelerated AI
  • AI accelerator offload — DSP & matrix accelerators
  • Offline model compilation & calibration
  • Open-source runtimes with accelerator delegates
  • CPU vs accelerator benchmarking
  • Live camera pipelines — classification & object detection
21AI in Production
  • Packaging models as system components
  • Deploying inference as a system service
  • Updating AI models over-the-air
  • Model versioning & on-target validation
  • Cross-platform performance benchmarking
22Securing the Boot Chain
  • Embedded threat modeling & industry benchmarks
  • Verified boot with signed boot images
  • Root filesystem integrity protection
23Runtime Hardening
  • Compiler hardening flags
  • User & permission lockdown
  • Syscall filtering
  • Service sandboxing
  • Mandatory access control
24Compliance & Release Security
  • CVE scanning in the build
  • SBOM generation
  • License compliance
  • Release security checklist & vulnerability management

LabsRecommended hardware

Hands-on labs run on real boards so you build and deploy the way it happens on the job.

BeagleBone AIAI-capable SBC for board bring-up & edge workloads.
Raspberry Pi 5Widely available board for Yocto images & peripheral labs.

Before you startPrerequisites

You should be comfortable with the GNU toolchain, Linux command-line skills and embedded-systems basics. A solid grounding in Linux systems engineering is strongly recommended — ideally TECH VEDA's Linux Systems Engineering program — so you are already fluent in processes, system calls, memory, file and device I/O, and how user space actually talks to the kernel. Embedded Linux work constantly crosses that user-space-to-kernel boundary, and engineers who already think in system-level terms pick up board bring-up, Yocto and real-world debugging far faster — and get noticeably more out of the hands-on labs.

AudienceWho should enroll

Embedded software & firmware engineersHardware / board engineersIoT & product engineersEdge-AI / on-device ML engineersR&D engineers & tech leads adopting custom Linux buildsEngineers shipping & updating fielded devicesEngineers targeting Embedded Linux / BSP rolesYocto / build-system engineersEdge / IoT platform engineersProduct / release engineers for connected devices

Your mentorLearn directly from the founder

Raghu Bharadwaj

Raghu Bharadwaj

Founder & Chief Mentor

75+ onsite trainings · 45+ enterprise clients · 10,000+ careers transformed since 2003. A thought leader in Embedded Linux education and the architect of TECH VEDA's hands-on training model.

ReviewsParticipant experiences

★★★★★

"Raghu Sir has this unique ability to keep our attention drawn to the overall framework of embedded Linux & drivers, even as we go deep into each interface and core concept."

SH
Shailesh
★★★★★

"Highly experienced and skilled in Linux kernel, device-driver development and the embedded domain. He knows exactly where students get stuck and helps you learn problem-solving approaches."

AN
Anupam
★★★★★

"The way Raghu Sir simplified the Yocto build system and made us work on every aspect practically has made building embedded Linux systems a cakewalk."

PV
Pavan

FAQsCommon questions

Can I target embedded product-development roles with these skills?+
Yes — these are industry-demanded skills, especially for roles such as Embedded Linux Engineer, Yocto Engineer, BSP Developer and Embedded Systems Developer.
Why learn Embedded Linux and Yocto together rather than separately?+
Embedded Linux gives you the foundation — boot process, kernel, device tree, rootfs. Yocto teaches you to build and customise complete distributions. This course blends both so you see how they complement each other in real product development.
I'm from a bare-metal background — do I need prior Linux knowledge?+
Some grounding helps a lot. Without core kernel understanding, embedded Linux stays procedural; proper Linux fundamentals greatly improve your ability to debug embedded issues and understand the development process. See Kernel Infrastructure.
What hardware do I need?+
Recommended boards are the BeagleBone AI and the Raspberry Pi 5.

Clients who engaged us for Embedded Linux

MurataAMDStryker Mercedes-BenzSiemensXilinx

Ready when you are

Talk to us about this program

Tell us your goal and background — we'll share the full curriculum, upcoming dates and combo pricing, and answer your questions. Pick whichever way is easiest for you.

  • Response within 1 business day
  • Full curriculum & fee details
  • Guidance on the right track / combo
  • EMI / UPI payment options