#CategorySubjectL-T-PCredits
1Professional CoreVLSI Design3-0-03
2Professional CoreMicroprocessors & Microcontrollers3-0-03
3Professional CoreDigital Signal Processing3-0-03
4Professional Elective-IIAnalog IC Design / Satellite Communication / Smart and Wireless Instrumentation / Machine Learning3-0-03
5Professional Elective-IIIBio-Medical Instrumentation / Microwave Engineering / Embedded Systems / Artificial Intelligence3-0-03
6Open Elective-II(department pool)3-0-03
7Professional CoreVLSI Design Lab0-0-31.5
8Professional CoreMicroprocessors & Microcontrollers Lab0-0-31.5
9Skill Enhancement CourseMachine Learning Lab0-1-22
10Audit CourseResearch Methodology and IPR2-0-0–
Total20-1-823

A Mandatory Industry Internship of 8 weeks during the summer vacation runs alongside this semester. The table again lists optional Minor/Honors rows (e.g., a Minors pool including Embedded System Design, Digital Signal Processing) that are add-on tracks, not expanded here.

VLSI Design

the chip-design course covering MOS device behaviour through to FPGA architecture, foundational for anyone heading into semiconductor or hardware design work.

  • Unit 1: MOS transistor electrical properties, CMOS fabrication basics, and stick diagrams/layout rules
  • Unit 2: Sheet resistance, area capacitance, propagation delay, and MOS circuit scaling
  • Unit 3: Analog IC building blocks — biasing styles and single-stage MOSFET amplifiers
  • Unit 4: Static and dynamic CMOS logic design — combinational and sequential circuits
  • Unit 5: FPGA design flow and architecture, plus advanced technologies (FinFET, TFET)

Microprocessors & Microcontrollers

traces the evolution from the 8086 through the 8051 to ARM Cortex-M, the processor families most embedded-systems work is still built on.

  • Unit 1: 8086 architecture — register organization and minimum/maximum mode operation
  • Unit 2: 8086 assembly programming, addressing modes, and interrupt service routines
  • Unit 3: 8086 interfacing — memory, 8255 PPI, 8251 USART, and DMA controllers
  • Unit 4: 8051 microcontroller architecture and interfacing (A/D, D/A, keyboard, LCD)
  • Unit 5: ARM Cortex-M3 architecture, programming model, and interrupt controller

Digital Signal Processing

teaches how signals are processed on digital hardware in practice, from z-transforms and FFTs to actual DSP processor architectures.

  • Unit 1: Discrete-time signals/systems and frequency-domain analysis of LTI systems
  • Unit 2: Z-transform properties and the Discrete Fourier Transform (DFT)
  • Unit 3: Fast Fourier Transform algorithms and structures for realizing FIR/IIR systems
  • Unit 4: FIR and IIR digital filter design methods (windowing, impulse invariance, bilinear transform)
  • Unit 5: Programmable DSP architecture and the TMS320C5X instruction set

Analog IC Design

(Professional Elective-II) — goes deeper into CMOS analog building blocks (op-amps, comparators, PLLs) than the core VLSI course, for students aiming at analog/mixed-signal design roles.

  • Unit 1: MOS device modelling — large-signal and small-signal transistor models
  • Unit 2: Analog CMOS sub-circuits — current mirrors, sinks/sources, and bandgap references
  • Unit 3: CMOS amplifier and op-amp design, including two-stage op-amp compensation
  • Unit 4: Comparator design and performance characterization
  • Unit 5: Oscillator and phase-locked loop design (ring, LC, charge-pump PLLs)

Satellite Communication

(Professional Elective-II) — covers how satellite links and constellations are engineered, from orbital mechanics to GPS/GNSS receiver operation.

  • Unit 1: Orbital mechanics, launch vehicles, and satellite communication basics
  • Unit 2: Satellite subsystems — attitude control, telemetry, and communication payloads
  • Unit 3: Satellite link design — link budget, C/N ratio, and system noise temperature
  • Unit 4: Multiple access techniques (FDMA, TDMA, CDMA) and earth station architecture
  • Unit 5: LEO/GEO satellite systems and GNSS (GPS, GLONASS, IRNSS) principles

Smart and Wireless Instrumentation

(Professional Elective-II) — applies wireless sensor network concepts to instrumentation, relevant for IoT and industrial monitoring applications.

  • Unit 1: Smart instrumentation and wireless sensor network (WSN) design constraints
  • Unit 2: Sensor node architecture — processor subsystems and communication interfaces
  • Unit 3: Wireless digital communication fundamentals — source/channel encoding and modulation
  • Unit 4: WSN hardware (Zigbee) and energy-harvesting power sources
  • Unit 5: WSN applications — structural health monitoring, healthcare, and precision agriculture

Machine Learning

(Professional Elective-II) — a first pass at ML concepts and workflow, increasingly core to how ECE graduates now approach signal and data-driven problems.

  • Unit 1: ML paradigms (supervised, unsupervised, reinforcement) and Python ML tooling
  • Unit 2: Exploratory data analysis, data cleaning, scaling, and feature engineering
  • Unit 3: Supervised learning algorithms — KNN, logistic regression, decision trees, ensembles, SVC
  • Unit 4: Unsupervised learning — K-means, hierarchical clustering, and DBSCAN
  • Unit 5: Model evaluation metrics, cross-validation, and data visualization techniques

Bio-Medical Instrumentation

(Professional Elective-III) — applies electronics to medical measurement, the discipline behind ECG/EEG machines and diagnostic imaging equipment.

  • Unit 1: Bioelectric potentials, electrodes, and biomedical signal basics
  • Unit 2: Cardiovascular measurement — ECG, blood pressure, and heart-sound analysis
  • Unit 3: Patient monitoring systems and respiratory measurement instrumentation
  • Unit 4: Bio-telemetry systems and clinical laboratory instrumentation
  • Unit 5: X-ray/radioisotope instrumentation, electrical safety, and modern imaging (MRI, ultrasound)

Microwave Engineering

(Professional Elective-III) — covers the high-frequency devices and waveguide theory used in radar, satellite, and point-to-point RF links.

  • Unit 1: Rectangular waveguide mode analysis and microstrip line fundamentals
  • Unit 2: Microwave tubes — 2-cavity and reflex klystrons
  • Unit 3: Helix TWTs and M-type tubes (magnetrons)
  • Unit 4: Waveguide components — couplers, attenuators, phase shifters, and S-matrix analysis
  • Unit 5: Microwave solid-state devices (Gunn diodes) and microwave bench measurements

Embedded Systems

(Professional Elective-III) — teaches how firmware and hardware come together in resource-constrained devices, core knowledge for product-level embedded design.

  • Unit 1: Embedded system classification, core components, and characteristics
  • Unit 2: Embedded hardware design — I/O types, serial/parallel communication devices
  • Unit 3: Embedded firmware design approaches, ISR handling, and device drivers
  • Unit 4: Real-time operating system concepts and hardware-software co-design
  • Unit 5: Embedded development tools, debugging, testing, and the end-to-end design flow

Artificial Intelligence

(Professional Elective-III) — a classical-AI survey (search, knowledge representation, reasoning) that complements the Machine Learning elective’s statistical approach.

  • Unit 1: State-space search and heuristic search techniques (hill climbing, best-first search)
  • Unit 2: Knowledge representation using predicate logic and rule-based systems
  • Unit 3: Reasoning under uncertainty — Bayesian networks and Dempster-Shafer theory
  • Unit 4: Fuzzy logic and slot-and-filler knowledge structures (semantic nets, frames, scripts)
  • Unit 5: Game-playing algorithms, planning systems, and connectionist (neural network) models

Open electives offered by the ECE department (Pool 2)

mapped to the Open Elective-II slot, these are additional subjects ECE offers to other branches:

  • Linear and Digital IC Applications — the same content as the III Year I Semester Analog & Digital IC Applications Professional Core subject above, offered to other departments.
  • Principles of Communications

    a condensed analog-communications course for non-ECE branches, covering the same modulation fundamentals from a systems-and-probability angle.

  • Unit 1: Fourier tools, autocorrelation, energy spectral density, and AM basics

  • Unit 2: DSB-SC and SSB modulation/demodulation, including the Hilbert transform
  • Unit 3: Angle modulation — FM/PM, Carson’s rule, and FM demodulation
  • Unit 4: Sampling, quantization, and delta/differential PCM
  • Unit 5: Probability basics and random processes as applied to wireless channels

  • Principles of Signal Processing

    a compact signals-and-systems-plus-DSP course for other branches, combining continuous-time transform theory with discrete filter design.

  • Unit 1: Signal/system classification and LTI system analysis via convolution

  • Unit 2: Fourier series/transform and Laplace transform of continuous-time signals
  • Unit 3: Sampling theorem, Z-transforms, and their region of convergence
  • Unit 4: Discrete Fourier Transform, Fast Fourier Transform (decimation in time/frequency)
  • Unit 5: IIR and FIR digital filter design (Butterworth, windowing techniques)

  • Microprocessors & Microcontrollers — the same 8086/8051/ARM content as the Professional Core subject above, offered to other departments.

VLSI Design Lab

CMOS schematic-to-layout design practice using industry EDA tools.

  • CMOS logic circuit design (inverter, universal gates, adders) with schematic and layout generation
  • Sequential circuit layout (latches, counters) and analog blocks (SRAM cell, differential amplifier, ring oscillator)

Microprocessors & Microcontrollers Lab

assembly-language programming and hardware interfacing across three processor generations.

  • 8086 assembly programs (arithmetic, sorting) and peripheral interfacing (ADC, DAC, stepper motor)
  • 8051 assembly programming, timer/UART operation, and sensor/LCD interfacing
  • ARM Cortex-M3 assembly programming using Keil MDK-ARM (timers, PWM, UART)

Machine Learning Lab

implements the classic ML algorithm set in Python against real datasets.

  • FIND-S, Candidate-Elimination, and ID3 decision-tree algorithm implementations
  • Regression, KNN, Naive Bayes, and neural-network (backpropagation) implementations
  • Clustering (K-Means, EM) and dimensionality reduction (PCA) exercises

Research Methodology and IPR

an audit course introducing how to frame a research problem and understand intellectual-property protection, relevant once students start project or thesis work.

  • Unit 1: Research problem formulation and criteria for a good research problem
  • Unit 2: Literature review methods, research ethics, and technical writing
  • Unit 3: Nature of intellectual property — patents, designs, trademarks, and copyright
  • Unit 4: Patent rights, licensing, and technology transfer
  • Unit 5: Recent developments in IPR, including software and biological-systems IP