*Core Courses* 

(Common for All Students) 

1. *Advanced Mathematics for Engineers* 

   - Linear algebra, optimization, numerical methods, stochastic processes. 

   - Applications in circuit design, signal processing, and control systems. 

 

2. *Advanced Electrical Circuits & Systems* 

   - Nonlinear circuits, network synthesis, distributed parameter systems. 

 

3. *Power Electronics & Drives* 

   - Converters (AC/DC, DC/DC), inverters, motor drives, renewable energy integration. 

 

4. *Digital Signal & Image Processing* 

   - Discrete-time systems, wavelet transforms, computer vision, real-time DSP applications. 

 

5. *VLSI Design & Embedded Systems* 

   - CMOS design, FPGA programming, System-on-Chip (SoC), ARM-based embedded systems. 

 

6. *Control Systems & Robotics* 

   - State-space modelling, adaptive control, robotic kinematics, industrial automation. 

 

7. *Electromagnetic Fields & Wave Propagation* 

   - Maxwell’s equations, antennas, RF/microwave engineering, optical communication. 

 

8. *Semiconductor Devices & Nanoelectronics* 

   - MOSFETs, MEMS, optoelectronics, quantum devices, fabrication techniques. 

 

9. *Research Methodology & Technical Communication* 

   - Thesis writing, grant proposals, data analysis tools (MATLAB, Python). 

 

*Specialization Tracks* 

(Choose 1–2 Focus Areas) 

 

*1. Power Systems & Renewable Energy* 

   - Smart grid technologies 

   - Energy storage systems (batteries, supercapacitors) 

   - High-voltage engineering 

   - Wind/solar energy systems 

   - Power system cybersecurity 

 

*2. Electronics & Embedded Systems* 

   - Analog/digital VLSI design 

   - IoT hardware and sensor networks 

   - Real-time operating systems (RTOS) 

   - MEMS/NEMS devices 

   - Low-power circuit design 

 

*3. Communications & Networking* 

   - 5G/6G wireless networks 

   - Optical fibre communication 

   - Satellite and radar systems 

   - Error-correcting codes 

   - Network security for IoT 

 

*4. Control, Automation & Robotics* 

   - Industrial robotics (PLC, SCADA) 

   - Autonomous vehicles and drones 

   - AI/ML for predictive control 

   - Swarm robotics 

   - Human-machine interfaces 

 

*5. Signal Processing & AI* 

   - Biomedical signal analysis 

   - Deep learning for computer vision 

   - Speech and audio processing 

   - Radar signal processing 

   - Reinforcement learning in control systems 

 

*6. Microelectronics & Photonics* 

   - Nanoelectronics and spintronics 

   - Photonic integrated circuits 

   - Semiconductor fabrication labs 

   - Quantum computing basics 

   - Advanced semiconductor modelling 

 

*Lab/Project Work* 

- *Advanced Labs*: 

  - Power electronics simulation (PSIM, PLECS) 

  - VLSI design (Cadence, Synopsys) 

  - Embedded systems (Arduino, Raspberry Pi, FPGA) 

  - RF/antenna design (ANSYS HFSS, CST) 

- *Capstone Project/Thesis*: 

  - Industry-sponsored projects (e.g., EV charging systems, smart grid prototypes). 

  - Original research (e.g., AI-driven power management, nano-sensor design). 

 

*Sample Semester-wise Structure* 

(2-Year Program Example) 

 

| *Year 1*                          | *Year 2*                          | 

|-------------------------------------|-------------------------------------| 

| *Semester 1*                      | *Semester 3*                      | 

| - Advanced Mathematics              | - Elective 3                        | 

| - Power Electronics                 | - Elective 4                        | 

| - VLSI Design                       | - Thesis/Project Phase I            | 

| *Semester 2*                      | *Semester 4*                      | 

| - Digital Signal Processing         | - Thesis/Project Phase II           | 

| - Control Systems                   | - Elective 5 (if required)          | 

| - Elective 1                        | - Industry Internship (optional)    | 

 

*Emerging Topics (Electives)* 

- Electric Vehicle Technology 

- AI/ML for Power Systems Optimization 

- Biomedical Instrumentation 

- Cybersecurity for Critical Infrastructure 

- Quantum Sensors and Devices 

- Edge Computing for IoT 

 

*Credit System* 

- *Total Credits*: 60–80 ECTS (varies by country). 

- *Breakdown*: 

  - Core Courses: 25–30 credits 

  - Electives: 20–25 credits 

  - Thesis/Project: 15–20 credits 

 

*Key Skills Developed* 

- Circuit design and simulation (PSpice, LTspice). 

- Embedded programming (C/C++, Verilog/VHDL). 

- Power system analysis (ETAP, MATLAB/Simulink). 

- Research and innovation in IoT, robotics, and smart grids.