Course Structure Overview
The Computer Applications program at Noida International University Greater Noida is structured over 8 semesters, combining core engineering subjects, departmental electives, science electives, and hands-on laboratory sessions. This structure ensures a balanced mix of theoretical knowledge and practical application, preparing students for careers in various domains of technology.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Computer Science | 3-0-0-3 | - |
| 1 | CS102 | Mathematics for Computing | 4-0-0-4 | - |
| 1 | CS103 | Programming Fundamentals | 3-0-0-3 | - |
| 1 | CS104 | Introduction to Data Structures | 3-0-0-3 | - |
| 1 | CS105 | Computer Organization and Architecture | 3-0-0-3 | - |
| 2 | CS201 | Data Structures and Algorithms | 4-0-0-4 | CS104 |
| 2 | CS202 | Database Management Systems | 3-0-0-3 | CS105 |
| 2 | CS203 | Operating Systems | 3-0-0-3 | CS105 |
| 2 | CS204 | Software Engineering | 3-0-0-3 | CS201 |
| 2 | CS205 | Object-Oriented Programming | 3-0-0-3 | CS103 |
| 3 | CS301 | Computer Networks | 3-0-0-3 | CS203 |
| 3 | CS302 | Web Technologies | 3-0-0-3 | CS204 |
| 3 | CS303 | Mobile Application Development | 3-0-0-3 | CS205 |
| 3 | CS304 | Artificial Intelligence | 3-0-0-3 | CS201 |
| 3 | CS305 | Cybersecurity Fundamentals | 3-0-0-3 | CS201 |
| 4 | CS401 | Machine Learning | 3-0-0-3 | CS304 |
| 4 | CS402 | Data Science | 3-0-0-3 | CS304 |
| 4 | CS403 | Cloud Computing | 3-0-0-3 | CS301 |
| 4 | CS404 | Internet of Things (IoT) | 3-0-0-3 | CS301 |
| 4 | CS405 | Human-Computer Interaction | 3-0-0-3 | CS204 |
| 5 | CS501 | Advanced Algorithms | 3-0-0-3 | CS201 |
| 5 | CS502 | Research Methodology | 3-0-0-3 | - |
| 5 | CS503 | Capstone Project I | 4-0-0-4 | CS401 |
| 5 | CS504 | Software Testing and Quality Assurance | 3-0-0-3 | CS204 |
| 5 | CS505 | Advanced Database Systems | 3-0-0-3 | CS202 |
| 6 | CS601 | Capstone Project II | 4-0-0-4 | CS503 |
| 6 | CS602 | Internship | 0-0-0-0 | - |
| 6 | CS603 | Special Topics in Computer Applications | 3-0-0-3 | CS501 |
| 6 | CS604 | Entrepreneurship and Innovation | 2-0-0-2 | - |
| 6 | CS605 | Professional Ethics in IT | 2-0-0-2 | - |
| 7 | CS701 | Advanced Machine Learning | 3-0-0-3 | CS401 |
| 7 | CS702 | Big Data Analytics | 3-0-0-3 | CS402 |
| 7 | CS703 | Distributed Systems | 3-0-0-3 | CS301 |
| 7 | CS704 | Advanced Cybersecurity | 3-0-0-3 | CS305 |
| 7 | CS705 | Mobile and Web Security | 3-0-0-3 | CS303 |
| 8 | CS801 | Research Thesis | 6-0-0-6 | CS502 |
| 8 | CS802 | Industry Project | 4-0-0-4 | CS601 |
| 8 | CS803 | Professional Development | 2-0-0-2 | - |
| 8 | CS804 | Capstone Presentation | 2-0-0-2 | CS601 |
| 8 | CS805 | Final Evaluation | 0-0-0-0 | - |
The curriculum is designed to build a strong foundation in computer science principles before moving into specialized areas. Each course integrates theory with practical lab sessions to ensure students can apply learned concepts effectively.
Advanced Departmental Elective Courses
Departmental electives offer advanced knowledge and skills in niche areas of Computer Applications. Here are some detailed descriptions:
- Machine Learning: This course delves into supervised and unsupervised learning techniques, neural networks, deep learning frameworks, and reinforcement learning algorithms. Students will gain hands-on experience with libraries like TensorFlow, PyTorch, and Scikit-learn.
- Data Science: Covering data collection, cleaning, analysis, visualization, and modeling, this course prepares students to handle large datasets and extract meaningful insights using tools like Python, R, and SQL.
- Cybersecurity: This course explores cryptographic techniques, network security protocols, ethical hacking, incident response strategies, and compliance standards. Students will engage in simulations and real-world case studies.
- Cloud Computing: Designed to provide an understanding of cloud infrastructure, virtualization, containerization, and deployment models, this course includes practical labs on AWS, Azure, and GCP platforms.
- Internet of Things (IoT): Students learn about sensor networks, embedded systems, wireless communication protocols, and IoT platform development. Labs involve building smart devices using Raspberry Pi and Arduino boards.
- Web Technologies: This course covers modern web frameworks like React, Angular, Node.js, and backend technologies including REST APIs, microservices architecture, and cloud hosting.
- Mobile Application Development: Focused on native and cross-platform development using Swift (iOS), Kotlin (Android), Flutter, and React Native, students will build mobile applications for various platforms.
- Human-Computer Interaction: This course examines user interface design principles, usability testing methods, accessibility standards, and interaction paradigms in digital environments. Students conduct research projects involving user studies and prototyping.
- Distributed Systems: Exploring concepts of distributed computing, parallel processing, fault tolerance, and consensus algorithms, this course includes hands-on projects using frameworks like Hadoop and Spark.
- Advanced Cybersecurity: A deep dive into advanced threat detection, penetration testing, security architecture design, and risk management. Students will analyze real-world cybersecurity incidents and propose mitigation strategies.
Project-Based Learning Philosophy
The department strongly believes in project-based learning as a core component of the educational experience. Projects are integrated throughout the curriculum to reinforce theoretical concepts with practical applications. The structure involves both individual and group projects, allowing students to develop teamwork, communication, and leadership skills.
Mini-projects are assigned during the second year, focusing on fundamental concepts such as database design or algorithm implementation. These projects are evaluated through presentations, peer reviews, and written documentation.
The final-year capstone project is a significant undertaking that spans multiple semesters. Students select topics aligned with their interests and career goals, working closely with faculty mentors. The project includes research, development, testing, documentation, and presentation components.
Faculty members guide students through the entire process, providing feedback on progress, suggesting improvements, and ensuring alignment with industry standards. Evaluation criteria include technical depth, innovation, feasibility, documentation quality, and final presentation.