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.