Curriculum Overview
The Skill Development program at Rungta International Skills University Durg is structured to provide a comprehensive and progressive learning experience over four years. The curriculum is designed to blend theoretical knowledge with practical application, ensuring that students are not only academically sound but also industry-ready. The program is divided into 8 semesters, each with a carefully curated set of courses that build upon one another to create a cohesive and robust educational framework.
The curriculum includes core courses, departmental electives, science electives, and laboratory sessions. Each course is designed to meet specific learning outcomes and contribute to the overall skill development of the students. The following table provides a detailed breakdown of all courses across the 8 semesters:
Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
---|---|---|---|---|
1 | ENG101 | English for Engineering | 3-0-0-3 | None |
1 | MAT101 | Calculus and Differential Equations | 4-0-0-4 | None |
1 | PHY101 | Physics for Engineers | 3-0-0-3 | None |
1 | CHE101 | Chemistry for Engineers | 3-0-0-3 | None |
1 | CS101 | Introduction to Programming | 2-0-2-3 | None |
1 | ESC101 | Engineering Drawing | 1-0-3-2 | None |
2 | MAT102 | Linear Algebra and Statistics | 4-0-0-4 | MAT101 |
2 | PHY102 | Electromagnetic Fields and Waves | 3-0-0-3 | PHY101 |
2 | CS102 | Data Structures and Algorithms | 3-0-2-4 | CS101 |
2 | EEE101 | Basic Electrical Engineering | 3-0-0-3 | None |
2 | ME101 | Engineering Mechanics | 3-0-0-3 | None |
2 | ESC102 | Engineering Graphics | 1-0-3-2 | ESC101 |
3 | CS201 | Database Management Systems | 3-0-2-4 | CS102 |
3 | CS202 | Computer Architecture | 3-0-0-3 | CS102 |
3 | CS203 | Operating Systems | 3-0-2-4 | CS102 |
3 | CS204 | Software Engineering | 3-0-2-4 | CS102 |
3 | CS205 | Web Technologies | 3-0-2-4 | CS102 |
3 | CS206 | Object-Oriented Programming | 3-0-2-4 | CS102 |
4 | CS301 | Machine Learning | 3-0-2-4 | CS201 |
4 | CS302 | Cybersecurity Fundamentals | 3-0-2-4 | CS203 |
4 | CS303 | Big Data Analytics | 3-0-2-4 | CS201 |
4 | CS304 | Advanced Algorithms | 3-0-0-3 | CS202 |
4 | CS305 | Network Security | 3-0-2-4 | CS203 |
4 | CS306 | Cloud Computing | 3-0-2-4 | CS203 |
5 | CS401 | Artificial Intelligence | 3-0-2-4 | CS301 |
5 | CS402 | Internet of Things (IoT) | 3-0-2-4 | CS204 |
5 | CS403 | Robotics and Automation | 3-0-2-4 | CS304 |
5 | CS404 | Quantitative Finance | 3-0-2-4 | CS201 |
5 | CS405 | Digital Transformation | 3-0-2-4 | CS203 |
5 | CS406 | Human-Computer Interaction | 3-0-2-4 | CS204 |
6 | CS501 | Advanced Machine Learning | 3-0-2-4 | CS401 |
6 | CS502 | Blockchain Technologies | 3-0-2-4 | CS205 |
6 | CS503 | Embedded Systems | 3-0-2-4 | CS202 |
6 | CS504 | Financial Engineering | 3-0-2-4 | CS404 |
6 | CS505 | Research Methodology | 2-0-0-2 | CS303 |
6 | CS506 | Project Management | 2-0-0-2 | CS204 |
7 | CS601 | Capstone Project I | 0-0-6-6 | CS505 |
7 | CS602 | Advanced Research | 0-0-6-6 | CS505 |
7 | CS603 | Internship | 0-0-0-12 | CS505 |
8 | CS701 | Capstone Project II | 0-0-6-6 | CS601 |
8 | CS702 | Industry Collaboration | 0-0-6-6 | CS602 |
8 | CS703 | Graduation Thesis | 0-0-0-12 | CS602 |
Advanced Departmental Electives
The department offers a wide range of advanced departmental electives that allow students to specialize in areas of interest and gain in-depth knowledge in specific fields. These courses are designed to align with current industry trends and emerging technologies, ensuring that students are equipped with the most relevant skills for their future careers.
1. Machine Learning
This course provides a comprehensive introduction to machine learning algorithms and their applications. Students will learn about supervised and unsupervised learning, neural networks, and deep learning techniques. The course includes hands-on projects involving real-world datasets and industry collaboration.
2. Cybersecurity Fundamentals
This course covers the principles and practices of cybersecurity. Students will explore topics such as network security, cryptography, ethical hacking, and risk management. The course includes practical sessions and simulations to enhance understanding.
3. Big Data Analytics
This course focuses on the tools and techniques used in big data analytics. Students will learn about data processing, visualization, and predictive modeling. The course includes projects involving real-world data from various industries.
4. Advanced Algorithms
This course delves into advanced algorithmic techniques and their applications. Students will study topics such as graph algorithms, dynamic programming, and optimization techniques. The course includes problem-solving sessions and coding challenges.
5. Network Security
This course explores the principles and practices of network security. Students will learn about firewalls, intrusion detection systems, and secure network design. The course includes practical sessions and real-world case studies.
6. Cloud Computing
This course covers the fundamentals of cloud computing and its applications. Students will learn about cloud architecture, deployment models, and service models. The course includes hands-on projects involving cloud platforms like AWS and Azure.
7. Artificial Intelligence
This course provides a comprehensive introduction to artificial intelligence and its applications. Students will learn about AI techniques, natural language processing, and computer vision. The course includes projects involving AI development and deployment.
8. Internet of Things (IoT)
This course explores the design and implementation of IoT systems. Students will learn about sensors, communication protocols, and cloud integration. The course includes lab-based projects involving physical prototyping and deployment.
9. Robotics and Automation
This course covers the principles and applications of robotics and automation. Students will learn about robot design, control systems, and automation technologies. The course includes hands-on projects involving physical robots and simulation tools.
10. Quantitative Finance
This course focuses on the application of mathematical and statistical methods in finance. Students will learn about financial modeling, risk management, and algorithmic trading. The course includes projects involving financial data analysis and predictive modeling.
11. Digital Transformation
This course explores the impact of digital technologies on business and society. Students will learn about digital strategy, innovation management, and change leadership. The course includes case studies and projects involving real-world organizations.
12. Human-Computer Interaction
This course focuses on the design and evaluation of user interfaces. Students will learn about user experience design, usability testing, and prototyping. The course includes projects involving user research and interface development.
13. Advanced Machine Learning
This course delves into advanced machine learning techniques and their applications. Students will study topics such as reinforcement learning, deep learning architectures, and natural language processing. The course includes research projects and industry collaboration.
14. Blockchain Technologies
This course explores the principles and applications of blockchain technology. Students will learn about distributed ledgers, smart contracts, and cryptocurrency systems. The course includes projects involving blockchain development and deployment.
15. Embedded Systems
This course covers the design and implementation of embedded systems. Students will learn about microcontrollers, real-time systems, and hardware-software integration. The course includes lab-based projects involving physical prototyping and deployment.
Project-Based Learning Framework
The department places a strong emphasis on project-based learning as a core component of the curriculum. This approach ensures that students gain practical experience and apply theoretical concepts to real-world problems.
The project-based learning framework includes mandatory mini-projects and a final-year thesis/capstone project. These projects are designed to be challenging, relevant, and collaborative, allowing students to work in teams and develop leadership skills.
Mini-Projects
Mini-projects are introduced in the second and third years of the program. These projects are typically completed in groups and are designed to reinforce learning outcomes from core courses. Students are required to work on projects that involve problem-solving, research, and practical implementation.
Final-Year Thesis/Capstone Project
The final-year thesis or capstone project is a comprehensive, industry-relevant initiative that serves as the culmination of the student's academic journey. Students work on projects that are often developed in collaboration with industry partners, ensuring that the research has real-world impact and relevance.
Project Selection and Mentorship
Students are encouraged to select projects based on their interests and career goals. The department provides a list of potential project ideas, and students can also propose their own projects with faculty mentorship. Faculty mentors are assigned based on the student's interests and the expertise of the faculty member.
Through this structured approach to project-based learning, students at Rungta International Skills University Durg are equipped with the skills and experience needed to succeed in their chosen careers and make meaningful contributions to their fields.