Curriculum Overview

The curriculum at Rungta International Skills University Durg is designed to provide a balanced and comprehensive education in engineering, combining theoretical knowledge with practical application and industry exposure. The program is structured over eight semesters, with a progressive increase in complexity and specialization. The curriculum is regularly updated based on feedback from industry partners and academic experts to ensure relevance and alignment with current trends.

Course Structure Across All 8 Semesters

Semester	Course Code	Course Title	Course Type	Credit Structure (L-T-P-C)	Prerequisites
1	ENG101	Engineering Mathematics I	Core	3-1-0-4	None
1	ENG102	Engineering Physics	Core	3-1-0-4	None
1	ENG103	Engineering Chemistry	Core	3-1-0-4	None
1	ENG104	Basic Electrical Engineering	Core	3-1-0-4	None
1	ENG105	Introduction to Programming	Core	3-1-0-4	None
1	ENG106	Engineering Graphics	Core	2-1-0-3	None
1	ENG107	Workshop Practice	Core	0-0-2-2	None
2	ENG201	Engineering Mathematics II	Core	3-1-0-4	ENG101
2	ENG202	Engineering Mechanics	Core	3-1-0-4	ENG102
2	ENG203	Electromagnetic Fields	Core	3-1-0-4	ENG104
2	ENG204	Signals and Systems	Core	3-1-0-4	ENG105
2	ENG205	Data Structures and Algorithms	Core	3-1-0-4	ENG105
2	ENG206	Computer Organization	Core	3-1-0-4	ENG105
2	ENG207	Engineering Materials	Core	3-1-0-4	ENG103
2	ENG208	Workshop Practice II	Core	0-0-2-2	ENG107
3	ENG301	Engineering Mathematics III	Core	3-1-0-4	ENG201
3	ENG302	Thermodynamics	Core	3-1-0-4	ENG202
3	ENG303	Control Systems	Core	3-1-0-4	ENG204
3	ENG304	Digital Electronics	Core	3-1-0-4	ENG203
3	ENG305	Database Management Systems	Core	3-1-0-4	ENG205
3	ENG306	Electrical Machines	Core	3-1-0-4	ENG203
3	ENG307	Strength of Materials	Core	3-1-0-4	ENG202
3	ENG308	Workshop Practice III	Core	0-0-2-2	ENG208
4	ENG401	Engineering Mathematics IV	Core	3-1-0-4	ENG301
4	ENG402	Heat Transfer	Core	3-1-0-4	ENG302
4	ENG403	Microprocessors	Core	3-1-0-4	ENG304
4	ENG404	Operating Systems	Core	3-1-0-4	ENG205
4	ENG405	Computer Networks	Core	3-1-0-4	ENG205
4	ENG406	Power Electronics	Core	3-1-0-4	ENG306
4	ENG407	Design of Structures	Core	3-1-0-4	ENG307
4	ENG408	Workshop Practice IV	Core	0-0-2-2	ENG308
5	ENG501	Advanced Mathematics	Core	3-1-0-4	ENG401
5	ENG502	Fluid Mechanics	Core	3-1-0-4	ENG302
5	ENG503	Embedded Systems	Core	3-1-0-4	ENG403
5	ENG504	Software Engineering	Core	3-1-0-4	ENG404
5	ENG505	Machine Learning	Core	3-1-0-4	ENG405
5	ENG506	Power Systems	Core	3-1-0-4	ENG306
5	ENG507	Structural Analysis	Core	3-1-0-4	ENG407
5	ENG508	Workshop Practice V	Core	0-0-2-2	ENG408
6	ENG601	Advanced Control Systems	Core	3-1-0-4	ENG303
6	ENG602	Advanced Thermodynamics	Core	3-1-0-4	ENG402
6	ENG603	Neural Networks	Core	3-1-0-4	ENG505
6	ENG604	Advanced Database Systems	Core	3-1-0-4	ENG305
6	ENG605	Advanced Power Electronics	Core	3-1-0-4	ENG406
6	ENG606	Advanced Structural Design	Core	3-1-0-4	ENG507
6	ENG607	Workshop Practice VI	Core	0-0-2-2	ENG508
7	ENG701	Research Methodology	Core	3-1-0-4	None
7	ENG702	Project Management	Core	3-1-0-4	None
7	ENG703	Advanced Electives I	Departmental Elective	3-1-0-4	None
7	ENG704	Advanced Electives II	Departmental Elective	3-1-0-4	None
7	ENG705	Advanced Electives III	Departmental Elective	3-1-0-4	None
7	ENG706	Advanced Electives IV	Departmental Elective	3-1-0-4	None
7	ENG707	Workshop Practice VII	Core	0-0-2-2	ENG607
8	ENG801	Final Year Project	Core	0-0-8-12	None
8	ENG802	Internship	Core	0-0-0-6	None
8	ENG803	Capstone Project	Core	0-0-8-12	None
8	ENG804	Elective Courses	Elective	3-1-0-4	None

Advanced Departmental Elective Courses

Advanced departmental electives are designed to provide students with specialized knowledge in their chosen fields. These courses are offered in the later semesters and are tailored to meet the demands of the industry and emerging trends in engineering.

Machine Learning

This course provides an in-depth understanding of machine learning algorithms and their applications. Students will learn about supervised and unsupervised learning, neural networks, deep learning, and reinforcement learning. The course includes hands-on projects and real-world applications, preparing students for careers in AI and data science.

Neural Networks

This course explores the principles and applications of neural networks, including feedforward networks, convolutional networks, and recurrent networks. Students will gain practical experience in designing and training neural networks using frameworks like TensorFlow and PyTorch.

Advanced Control Systems

This course covers advanced topics in control systems, including state-space representation, optimal control, and robust control. Students will learn to design and analyze control systems for complex engineering applications.

Advanced Thermodynamics

This course delves into advanced thermodynamic concepts, including thermodynamic cycles, refrigeration, and gas dynamics. Students will explore real-world applications and develop skills in thermodynamic analysis and design.

Embedded Systems

This course provides a comprehensive overview of embedded systems, including microcontroller architecture, real-time operating systems, and embedded software development. Students will gain practical experience in designing and implementing embedded systems.

Advanced Database Systems

This course covers advanced topics in database systems, including query optimization, transaction management, and distributed databases. Students will learn to design and implement efficient database systems for large-scale applications.

Advanced Power Electronics

This course explores advanced power electronics circuits and systems, including power converters, inverters, and motor drives. Students will gain practical experience in designing and analyzing power electronic systems.

Advanced Structural Design

This course focuses on advanced structural design principles, including seismic design, wind load analysis, and structural optimization. Students will learn to design structures that can withstand various environmental loads.

Advanced Electrical Machines

This course covers advanced topics in electrical machines, including synchronous and induction machines, transformers, and special-purpose machines. Students will gain in-depth knowledge of machine design and analysis.

Advanced Fluid Mechanics

This course explores advanced fluid mechanics concepts, including turbulence, boundary layer theory, and computational fluid dynamics. Students will learn to analyze and design fluid systems for various applications.

Advanced Computer Networks

This course covers advanced topics in computer networks, including network security, wireless networks, and network protocols. Students will gain practical experience in designing and managing complex network systems.

Project-Based Learning Philosophy

The department emphasizes project-based learning as a core component of the engineering education. This approach ensures that students gain hands-on experience and develop practical skills that are essential for their future careers. The project-based learning model includes both mini-projects and a final-year thesis, providing students with a comprehensive understanding of engineering principles and their applications.

Mini-Projects

Mini-projects are assigned in the early semesters to help students apply theoretical concepts to practical problems. These projects are typically completed in groups and are evaluated based on technical content, presentation, and teamwork. The projects are designed to be challenging yet achievable, allowing students to build confidence and develop problem-solving skills.

Final-Year Thesis/Capstone Project

The final-year thesis or capstone project is a significant component of the program, providing students with an opportunity to work on a comprehensive engineering problem. Students work closely with faculty mentors to select a project topic, develop a research plan, and execute the project. The project is evaluated based on originality, technical depth, and presentation quality. The capstone project often leads to publications or patents, providing students with a strong foundation for their future careers.

Project Selection and Faculty Mentorship

Students are encouraged to select projects that align with their interests and career goals. The department provides a wide range of project topics, including industry-sponsored projects, research projects, and innovation challenges. Faculty mentors are assigned based on the student's project topic and expertise, ensuring that students receive guidance and support throughout their project journey.