Curriculum Overview
The Engineering program at People S University Bhopal is designed to provide a comprehensive academic foundation while offering flexibility for students to explore specialized areas of interest. The curriculum spans eight semesters and includes core courses, departmental electives, science electives, and laboratory sessions that collectively prepare students for careers in various engineering domains.
Course Listing by Semester
| Semester | Course Code | Full Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-0-2-4 | None |
| 1 | ENG102 | Engineering Physics I | 3-0-2-4 | None |
| 1 | ENG103 | Engineering Chemistry I | 3-0-2-4 | None |
| 1 | ENG104 | Basic Electrical Engineering | 3-0-2-4 | None |
| 1 | ENG105 | Introduction to Programming | 3-0-2-4 | None |
| 1 | ENG106 | Engineering Graphics and Design | 3-0-2-4 | None |
| 1 | ENG107 | English for Engineers | 3-0-2-4 | None |
| 2 | ENG201 | Engineering Mathematics II | 3-0-2-4 | ENG101 |
| 2 | ENG202 | Engineering Physics II | 3-0-2-4 | ENG102 |
| 2 | ENG203 | Engineering Chemistry II | 3-0-2-4 | ENG103 |
| 2 | ENG204 | Electrical Circuits and Networks | 3-0-2-4 | ENG104 |
| 2 | ENG205 | Data Structures and Algorithms | 3-0-2-4 | ENG105 |
| 2 | ENG206 | Engineering Mechanics | 3-0-2-4 | None |
| 2 | ENG207 | Communication Skills for Engineers | 3-0-2-4 | None |
| 3 | ENG301 | Engineering Mathematics III | 3-0-2-4 | ENG201 |
| 3 | ENG302 | Thermodynamics and Heat Transfer | 3-0-2-4 | ENG202 |
| 3 | ENG303 | Mechanics of Materials | 3-0-2-4 | ENG206 |
| 3 | ENG304 | Digital Electronics | 3-0-2-4 | ENG204 |
| 3 | ENG305 | Computer Organization and Architecture | 3-0-2-4 | ENG205 |
| 3 | ENG306 | Engineering Economy | 3-0-2-4 | None |
| 3 | ENG307 | Professional Ethics and Values | 3-0-2-4 | None |
| 4 | ENG401 | Engineering Mathematics IV | 3-0-2-4 | ENG301 |
| 4 | ENG402 | Fluid Mechanics and Hydraulic Machines | 3-0-2-4 | ENG302 |
| 4 | ENG403 | Machine Design | 3-0-2-4 | ENG303 |
| 4 | ENG404 | Analog Electronics | 3-0-2-4 | ENG304 |
| 4 | ENG405 | Software Engineering and Project Management | 3-0-2-4 | ENG305 |
| 4 | ENG406 | Industrial Training | 0-0-0-2 | None |
| 4 | ENG407 | Entrepreneurship Development | 3-0-2-4 | None |
| 5 | ENG501 | Probability and Statistics for Engineers | 3-0-2-4 | ENG401 |
| 5 | ENG502 | Control Systems | 3-0-2-4 | ENG402 |
| 5 | ENG503 | Signals and Systems | 3-0-2-4 | ENG401 |
| 5 | ENG504 | Microprocessors and Microcontrollers | 3-0-2-4 | ENG404 |
| 5 | ENG505 | Advanced Computer Architecture | 3-0-2-4 | ENG405 |
| 5 | ENG506 | Research Methodology | 3-0-2-4 | None |
| 5 | ENG507 | Engineering Management | 3-0-2-4 | None |
| 6 | ENG601 | Advanced Mathematics for Engineers | 3-0-2-4 | ENG501 |
| 6 | ENG602 | System Modeling and Simulation | 3-0-2-4 | ENG502 |
| 6 | ENG603 | Digital Signal Processing | 3-0-2-4 | ENG503 |
| 6 | ENG604 | Embedded Systems Design | 3-0-2-4 | ENG504 |
| 6 | ENG605 | Artificial Intelligence and Machine Learning | 3-0-2-4 | ENG505 |
| 6 | ENG606 | Capstone Project I | 3-0-2-4 | None |
| 7 | ENG701 | Advanced Control Systems | 3-0-2-4 | ENG602 |
| 7 | ENG702 | Pattern Recognition and Machine Learning | 3-0-2-4 | ENG603 |
| 7 | ENG703 | Neural Networks and Deep Learning | 3-0-2-4 | ENG604 |
| 7 | ENG704 | Cybersecurity Fundamentals | 3-0-2-4 | ENG605 |
| 7 | ENG705 | Internet of Things (IoT) | 3-0-2-4 | None |
| 7 | ENG706 | Capstone Project II | 3-0-2-4 | ENG606 |
| 8 | ENG801 | Advanced Topics in Engineering | 3-0-2-4 | ENG701 |
| 8 | ENG802 | Final Year Project | 3-0-2-4 | ENG706 |
| 8 | ENG803 | Industry Internship | 0-0-0-4 | None |
| 8 | ENG804 | Project Presentation and Defense | 3-0-2-4 | ENG802 |
Detailed Departmental Elective Courses
Departmental electives in the Engineering program at People S University Bhopal offer students a chance to delve deeper into specialized areas. Here are descriptions of several advanced courses:
- Advanced Computer Architecture: This course explores modern processor designs, memory hierarchies, parallel processing architectures, and performance optimization techniques. Students engage in simulations using tools like Gem5 and conduct experiments to understand microarchitecture concepts.
- Neural Networks and Deep Learning: Focusing on building and training neural networks for complex tasks such as image recognition and natural language understanding, this course covers backpropagation, convolutional layers, recurrent networks, and transformer models. Students implement projects using TensorFlow and PyTorch frameworks.
- Cybersecurity Fundamentals: Designed to give students a comprehensive overview of cybersecurity principles, including network security, cryptography, access control mechanisms, and threat analysis. Practical labs involve setting up secure networks and analyzing real-world attacks.
- Pattern Recognition and Machine Learning: This course delves into algorithms for pattern recognition, classification, regression, and clustering. Students apply these techniques to real datasets using scikit-learn, MATLAB, and Python-based ML libraries.
- Internet of Things (IoT): An exploration of IoT technologies, including sensors, actuators, wireless communication protocols, edge computing, and cloud integration. Labs involve developing IoT applications using Arduino and Raspberry Pi platforms.
- Embedded Systems Design: Covers design principles for embedded systems in automotive, medical, consumer electronics, and industrial automation. Students build prototypes using ARM Cortex-M processors and develop real-time operating system kernels.
- Digital Signal Processing: Focuses on digital signal processing techniques for audio, image, and biomedical signals. Topics include filtering, Fourier transforms, and spectral analysis with practical implementation using MATLAB and DSP libraries.
- Advanced Control Systems: Builds upon introductory control theory to explore modern control strategies such as state-space methods, optimal control, robust control, and nonlinear systems. Students model and simulate control systems using Simulink and Python-based tools.
- System Modeling and Simulation: Introduces students to modeling complex engineering systems using simulation software like MATLAB/Simulink, Arena, and AnyLogic. This course emphasizes the importance of simulation in predicting system behavior under various conditions.
- Artificial Intelligence and Machine Learning: A foundational course covering machine learning algorithms, including supervised, unsupervised, and reinforcement learning methods. Students learn to implement algorithms using Python libraries like scikit-learn, TensorFlow, and Keras.
Project-Based Learning Philosophy
The Engineering program at People S University Bhopal emphasizes project-based learning as a central pedagogical approach. This philosophy encourages students to solve real-world problems through collaborative research and innovation.
Mini-projects are assigned in the third and fourth semesters, allowing students to explore specific engineering challenges within their chosen domain. These projects typically span 2–3 months and involve working in teams under faculty guidance. Students must submit progress reports, present findings, and document their methodologies and outcomes.
The final-year thesis or capstone project represents the culmination of the student’s learning journey. It involves an independent research effort where students propose a problem statement, conduct literature reviews, design experiments, collect data, analyze results, and present solutions to a panel of faculty experts. The project is often guided by a faculty mentor who provides technical expertise and feedback throughout the process.
Students are encouraged to select projects that align with their career interests or address industry-relevant issues. They may choose to collaborate with faculty members conducting research projects, work on initiatives supported by external organizations, or even initiate entrepreneurial ventures. The university supports this through resources such as grant funding for student-led projects, access to research labs, and mentorship from senior researchers.
This approach not only reinforces theoretical knowledge but also develops essential soft skills such as teamwork, communication, time management, and leadership. It prepares students for the demands of professional engineering practice where problem-solving and innovation are paramount.