PG Diploma - Embedded & Automotive System With Agentic AI
( A Placement Oriented Program )
Drive the Future of Intelligent Mobility with Industry-Ready Skills.
100 % Placement Opportunities with
| Hands-On Projects Industry | Recognised Certification
Eligibility: BE, B.Tech, ME, M.Tech in ECE, EEE, E&I
(Graduate/Under Graduate /Working Professional)
Where embedded depth meets automotive grade and AI-native engineering
Most programs stop at microcontrollers. This one combines real embedded software, automotive systems, Linux and agentic AI—designed from bare metal to production-grade engineering.
Embedded depth
MCUs, C/C++, device drivers, RTOS, memory, buses, GPIO, timers and peripherals.
Automotive grade
CAN, LIN, diagnostics, AUTOSAR concepts and model-based engineering.
Agentic AI edge
LLM integration, tool use, workflow automation and AI-assisted engineering.
Firmware built to work
From bare-metal to RTOS and debugging, built around realistic tasks.
Real hardware, every track
Hands-on MCU, embedded Linux and peripheral integration exercises.
Industry toolchains
GCC, GDB, OpenOCD, CMake, Git and embedded development workflows.
Product-ready mindset
Requirements, debugging, reliability and maintainable embedded software.
Personality & AI skills
Engineering communication, documentation and AI-supported workflows.
Three capstones
Progressive projects from firmware to automotive and AI-enabled systems.
500 hours · 6 tracks · 17 modules · 3 capstones
Hardware Foundations → Core Programming → Embedded Software → Firmware & Drivers → Embedded Automotive → Agentic AI for Embedded Engineering
Electronics & Hardware Familiarization
Digital, analog and hardware foundations
Core Electronics: Analog Circuits to Digital Logic Design
Understand circuit basics, signals, logic and the hardware beneath embedded systems.
Key topics
- Voltage, current, resistance and circuit fundamentals.
- Diodes, rectifiers, Zener and transistor basics.
- Digital number systems and Boolean algebra.
- Logic gates, combinational circuits and simplification.
- Flip-flops, counters and sequential logic.
- Microcontroller architecture and digital interfaces.
- GPIO, timers, interrupts and peripheral fundamentals.
- Reading basic datasheets and circuit diagrams.
Core Programming & Problem Solving
C/C++, problem-solving and coding fundamentals
Mastering C Programming for MISRA-C Guidelines
Build reliable C programming skills for embedded development.
Key topics
- Data types, variables and operators.
- Control flow, loops and functions.
- Arrays, pointers and strings.
- Structures, unions and enums.
- Memory, scope and storage classes.
- Bitwise operations and register manipulation.
- Debugging and defensive coding.
- Introduction to MISRA-C principles.
C++ for Problem Solving & OOP
Apply object-oriented thinking and problem-solving patterns.
Key topics
- Classes, objects and encapsulation.
- Inheritance, polymorphism and abstraction.
- Constructors, destructors and object lifetime.
- References, pointers and memory management.
- Templates and standard library basics.
- Algorithms, data structures and complexity.
- Debugging and problem-solving practice.
Capstone 1: Problem-Solving Project
Apply C/C++ fundamentals to a small, structured engineering task.
Project details
- Break down a practical problem into functions and modules.
- Implement, test and debug the solution.
- Document decisions and demonstrate the result.
Embedded Software Programming
Embedded C, MCU architecture and RTOS
Embedded C Programming
Control hardware with efficient and predictable firmware.
Key topics
- Embedded C and cross-compilation basics.
- Memory-mapped registers and bit manipulation.
- Interrupts, ISRs and interrupt latency.
- Timers, counters and PWM.
- GPIO, ADC, DAC and peripheral interfaces.
- Volatile, const and memory-safe practices.
- Build, flash and debug workflows.
- Firmware structure and modular design.
Modern C++ for Embedded Systems
Use modern C++ features with embedded resource constraints in mind.
Key topics
- Modern C++ syntax and type safety.
- RAII, constructors and destructors.
- Templates and compile-time techniques.
- Resource management and memory constraints.
- Object-oriented firmware design.
- Testing, debugging and code quality.
Linux System Programming
Build software that uses core Linux APIs and services.
Key topics
- Processes, threads and scheduling.
- File descriptors and file I/O.
- Signals, pipes and inter-process communication.
- Sockets and network programming basics.
- System calls and permissions.
- Build tools and debugging on Linux.
Advanced C/C++ & Data Structures
Strengthen implementation skills for performance-conscious systems.
Key topics
- Linked lists, stacks, queues and trees.
- Searching, sorting and complexity.
- Dynamic memory and resource ownership.
- Bit manipulation and low-level techniques.
- Unit testing and code analysis.
- Performance-aware implementation.
Embedded Firmware & Driver Development
Drivers, peripherals, RTOS and hardware interfaces
Embedded Protocols & Peripheral Driver Development
Develop and debug peripheral drivers for microcontroller platforms.
Key topics
- Peripheral driver architecture.
- GPIO and external interrupts.
- UART, SPI and I²C driver concepts.
- Device communication and error handling.
- ADC, PWM and timer drivers.
- DMA concepts and efficient transfers.
- Testing and hardware-level debugging.
Embedded RTOS (FreeRTOS) and Advanced Programming
Design responsive firmware using real-time operating-system concepts.
Key topics
- Tasks, priorities and scheduling.
- Queues, semaphores and mutexes.
- Task notifications and event groups.
- Interrupt-to-task communication.
- Timing, latency and real-time constraints.
- Stack sizing, watchdogs and fault handling.
- Debugging concurrent firmware.
Capstone 2: Project — Firmware
Integrate drivers, peripherals and firmware into a working embedded application.
Project details
- Define hardware and firmware requirements.
- Build a modular driver and application structure.
- Test behavior and document the result.
Embedded Automotive
Automotive programming, networks and model-based design
Automotive Programming & AUTOSAR Foundation
Explore automotive software architecture and in-vehicle communication.
Key topics
- Automotive embedded system overview.
- CAN and LIN communication.
- UDS diagnostics and fault codes.
- AUTOSAR Classic concepts.
- ECU software architecture and layers.
- Requirements, traceability and testing.
- Automotive safety and reliability concepts.
Model-Based Design using MATLAB
Model and simulate embedded control systems and workflows.
Key topics
- MATLAB fundamentals and data handling.
- Simulink models and simulation.
- Control logic and state machines.
- Model validation and test cases.
- Model-based development workflow.
- Code-generation concepts and integration.
Agentic AI for Embedded Engineering
AI, automation, edge intelligence and applied capstone
Python for AI & Agentic AI
Use Python to build AI-enabled workflows and engineering tools.
Key topics
- Python foundations and data handling.
- APIs, packages and environment setup.
- LLM concepts and prompt engineering.
- Tool calling and structured outputs.
- Agent workflows and orchestration.
- Evaluation, logging and safe execution.
AI-Assisted Firmware & RTOS Development
Apply AI assistance to firmware development and debugging workflows.
Key topics
- AI support for code explanation and review.
- Generating tests and documentation.
- Debug-log analysis and root-cause support.
- RTOS task and timing analysis concepts.
- Validation of AI-generated code.
- Security, privacy and engineering oversight.
Real-Time Machine Learning & Edge AI
Explore deployment of compact machine-learning models on embedded platforms.
Key topics
- ML foundations for embedded systems.
- Inference constraints and model size.
- Sensor data and feature processing.
- Edge deployment and optimization.
- Latency, memory and power trade-offs.
- Model evaluation and reliability.
AI-Driven Embedded Capstone Project
Combine embedded software with an AI-enabled feature or engineering workflow.
Project details
- Define a real-world embedded use case.
- Integrate firmware, sensors or edge inference.
- Document tests, results and limitations.
Tools, platforms & hardware
Capabilities you’ll graduate with
Practical skills across embedded C/C++, real-time firmware, automotive systems and AI-assisted engineering.
Build firmware from the ground up — write clear, testable embedded C.
Control hardware directly — GPIO, timers, interrupts and peripherals.
Connect devices and systems — UART, SPI, I²C, CAN and LIN.
Engineer real-time software — tasks, scheduling and RTOS synchronization.
Work with Linux and C++ — system APIs, modern C++ and debugging.
Apply automotive concepts — AUTOSAR foundations and diagnostics.
Use AI responsibly — assist coding, testing and engineering workflows.
Explore edge intelligence — deploy and assess compact ML models.
Ship end-to-end projects — document, test and demonstrate working solutions.
Projects you’ll ship
| Project | Skills developed |
|---|---|
| Embedded GPIO and Peripheral Driver | Register-level firmware, peripheral control |
| RTOS-Based Embedded Application | Tasks, synchronization, real-time behavior |
| CAN/LIN Automotive Project | In-vehicle communication and diagnostics |
| Embedded Linux Application | System programming and integration |
| AI-Assisted Firmware Workflow | Tool calling, code review and test support |
| Edge AI / ML Prototype | Model deployment and performance evaluation |
Project selection and implementation depth may depend on the course delivery plan and learner progress.
Three certifications, one progression
Programming & Embedded C
Core C/C++ skills, low-level programming and embedded foundations.
Embedded Systems & Automotive
Firmware, RTOS, drivers and automotive software concepts.
AI-Powered Embedded & Agentic AI
AI-assisted engineering, edge intelligence and applied project work.
Assessments and project reviews help learners demonstrate practical skills across the program.
Built for embedded, automotive and embedded AI careers
Industry-focused learning and project experience for high-growth embedded, automotive and edge-AI roles.
Learn
Structured modules, technical resources and guided self-paced practice.
Practice
Hands-on firmware work, RTOS exercises, hardware labs and guided projects.
Assess
Domain assessments, skill-gap analysis and interview preparation.
Get placement-ready
Interview preparation, resume and project readiness, and job-search support.
Industry job roles
Industries hiring
Automotive electronics, IoT and connected devices, industrial automation, consumer electronics, robotics, embedded product engineering and edge-AI applications.
Who should enroll?
ECE, EEE, CSE and related students or graduates interested in embedded software, automotive electronics and AI-enabled devices.
Fresh graduates and early-career engineers who want hands-on skills in C/C++, firmware, RTOS, Linux or edge AI.
Hiring Client
Frequently asked questions
What is the duration of the PG Diploma in Embedded & Automotive Systems with Agentic AI?
The program runs for a total of 500 hours, delivered offline and instructor-led.
How is this PG Diploma different from a diploma in embedded systems?
Beyond embedded C, ARM Cortex-M drivers and FreeRTOS, it adds an Embedded Automotive track (CAN, LIN, ISO 26262, AUTOSAR and MATLAB/Simulink model-based design) and an Agentic AI track for AI-assisted firmware development, debugging and verification.
What automotive topics are covered?
ECUs, sensors and actuators, CAN architecture and programming, CAN analysis with BUSMASTER, LIN bus, ISO 26262 functional safety and ASIL levels, Classic and Adaptive AUTOSAR, and model-based design for ECUs with automatic code generation.
What will I learn in Agentic AI for embedded engineering?
AI coding agents for embedded C/C++, hardware-aware RAG, Model Context Protocol (MCP), AI agents with FreeRTOS and Zephyr, AI-based board bring-up and fault analysis, and AI-driven hardware-in-the-loop testing.
How many certifications and capstones are included?
The program includes 3 certifications and 3 capstone projects: programming, hardware and an AI-driven embedded capstone.
What jobs can I apply for after the program?
Roles include Embedded Systems Engineer, Embedded Software Developer, Linux Embedded Engineer, Hardware Engineer, Embedded AI Engineer, Automotive Software Developer and Graduate Engineer Trainee (Embedded).
