A structured, Learning path through the Automotive Embedded software stack β from vehicle electronics and middleware concepts, through CAN and Classic AUTOSAR architecture, to Basic Software integration and the C++ internals that power production middleware.
We have organized the content to go from system-level breadth to implementation-level depth, so you build the mental models first and the hands-on configuration and coding skills next.












Experiments are performed on one of the following Hardware (or the Emulator option available on QEMU). The hardware is not included and needs to be bought separately.



This course introduces the role of middleware in modern automotive embedded systems, covering architectures, real-world examples, and controller vs processor-based designs. Learn driver vs middleware code level differences, Covering the middleware example with a SOME/IP case study, OS essentials required for middleware development, why C++ dominates middleware development, and a clear learning roadmap for aspiring embedded middleware engineers.

This course provides a structured, end-to-end understanding of modern vehicle electronics β from foundational E/E architecture and sensors to advanced vehicle diagnostics, software stacks, and the latest automotive trends. The curriculum blends theory, systems engineering, and hands-on demos to provide a broader perspective on roles in automotive embedded systems, diagnostics, and E/E system development.
This program is ideal for engineering students, automotive professionals, and embedded system developers who want to explore the automotive system and software development ecosystem. It helps participants understand the industry-ready skills required for the next generation of vehicles β including EVs, ADAS, and SDVs.
This course builds a ground-up understanding of the CAN protocol β from network topology and bit timing to framing, arbitration, error handling, and CAN FD β the foundation every automotive and embedded communications engineer needs.
By connecting bus-level electrical behavior with frame structure, error detection, and protocol state machines, this course prepares you to read CAN traces, debug bus issues, and reason confidently about CAN-based systems.

This course builds the C-language foundation every AUTOSAR Classic engineer needs β memory model, linker behavior, startup sequence, pointers, type systems, and preprocessor patterns β all grounded in real AUTOSAR conventions and code you'll actually encounter in production stacks.
By connecting core C fundamentals with AUTOSAR-specific practices like MemMap sections, reentrancy, ISR handling, and MISRA-aligned defensive programming, this course prepares you to read, debug, and write AUTOSAR-compliant C code with confidence.

This course builds a ground-up understanding of Classic AUTOSAR β why it exists, how the ecosystem and documentation are organized, how the development methodology actually works, and how the metamodel and ARXML underpin every tool and workflow you'll use.
By walking through layered architecture, VFB, ports and interfaces, SWC types, and runnable/RTE internals with demos and case studies, this course prepares you to read, configure, and reason about AUTOSAR-based software with confidence.

This course takes you through the Basic Software layer of Classic AUTOSAR end to end β OS services, the communication stack, ECU state management, the memory stack, diagnostics, the crypto stack with SecOC, and MCAL β connecting architecture to real ARXML configuration at every stage.
By working through module interactions, configuration workflows, and real-world data flows across BSW, this course prepares you to integrate, configure, and debug AUTOSAR Basic Software with confidence.

This course unpacks the complete compilation pipeline, memory layout, symbol resolution, object lifetime, abstraction mechanisms, and performance behavior. You will analyze real binaries, inspect assembly output, and use professional tools like nm, objdump, and profilers to understand how design choices affect execution.
By connecting theory with system-level realities, this course builds strong mental models that help you write efficient, maintainable, and production-grade C++ codeβespecially for embedded systems, middleware, and performance-critical software.


Jegan is an Automotive Embedded Systems/Software trainer holding a Master's degree in Automotive Electronics, with 14+ years of experience spanning academia and industry. In academia, served as Assistant Professor teaching Automotive Control Systems, Electric Hybrid Vehicles, and Vehicle Dynamics while establishing a research laboratory for Rapid Control Prototyping and Hardware-in-the-Loop simulation. Guided a Formula Student electric race car project competing at international events in Italy and India.
In industry, progressed through senior roles designing competency frameworks for automotive business units, leading Model-Based Development tools creation, and managing technical delivery across diverse client segments. Currently leading the Embedded and Automotive track within a global talent development function, shaping the next generation of automotive software professionals.
Research interests focus on control strategy development for autonomous vehicles, vehicle dynamics and control, modern automotive software architectures, and vehicle software development. Continues serving on academic boards for automotive electronics programs, bridging industry innovation with academic excellence.

