Curriculum Overview
The Computer Science curriculum at North East Frontier Technical University West Siang is meticulously designed to provide students with a strong foundation in both theoretical and practical aspects of computing. The program spans eight semesters and integrates core subjects, departmental electives, science electives, and laboratory sessions to create a comprehensive learning experience.
Course Structure
The curriculum is structured across eight semesters with each semester consisting of core courses, departmental electives, science electives, and laboratory components. Students are required to complete all core courses before moving on to advanced topics in their third year.
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming Using C/C++ | 3-0-0-3 | - |
| 1 | CS102 | Mathematics for Computer Science | 3-0-0-3 | - |
| 1 | CS103 | Computer Organization and Architecture | 3-0-0-3 | - |
| 1 | CS104 | Introduction to Data Structures | 3-0-0-3 | CS101 |
| 1 | CS105 | English for Technical Communication | 2-0-0-2 | - |
| 1 | CS106 | Lab: Introduction to Programming | 0-0-3-1 | CS101 |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS104 |
| 2 | CS202 | Discrete Mathematics | 3-0-0-3 | CS102 |
| 2 | CS203 | Database Systems | 3-0-0-3 | CS104 |
| 2 | CS204 | Operating Systems | 3-0-0-3 | CS103 |
| 2 | CS205 | Software Engineering | 3-0-0-3 | - |
| 2 | CS206 | Lab: Data Structures and Algorithms | 0-0-3-1 | CS201 |
| 3 | CS301 | Computer Networks | 3-0-0-3 | CS204 |
| 3 | CS302 | Design and Analysis of Algorithms | 3-0-0-3 | CS201 |
| 3 | CS303 | Artificial Intelligence and Machine Learning | 3-0-0-3 | CS201 |
| 3 | CS304 | Cybersecurity Fundamentals | 3-0-0-3 | CS203 |
| 3 | CS305 | Human-Computer Interaction | 3-0-0-3 | - |
| 3 | CS306 | Lab: Computer Networks | 0-0-3-1 | CS301 |
| 4 | CS401 | Advanced Algorithms | 3-0-0-3 | CS201 |
| 4 | CS402 | Data Mining and Big Data Analytics | 3-0-0-3 | CS201 |
| 4 | CS403 | Cloud Computing | 3-0-0-3 | CS301 |
| 4 | CS404 | Internet of Things (IoT) | 3-0-0-3 | - |
| 4 | CS405 | Quantum Computing | 3-0-0-3 | - |
| 4 | CS406 | Lab: Machine Learning | 0-0-3-1 | CS303 |
| 5 | CS501 | Machine Learning and Deep Learning | 3-0-0-3 | CS303 |
| 5 | CS502 | Network Security | 3-0-0-3 | CS304 |
| 5 | CS503 | Data Visualization and Analytics | 3-0-0-3 | CS201 |
| 5 | CS504 | Software Architecture and Design Patterns | 3-0-0-3 | CS205 |
| 5 | CS505 | Research Methodology | 3-0-0-3 | - |
| 5 | CS506 | Lab: Software Engineering | 0-0-3-1 | CS205 |
| 6 | CS601 | Advanced Cybersecurity | 3-0-0-3 | CS304 |
| 6 | CS602 | Mobile Application Development | 3-0-0-3 | CS101 |
| 6 | CS603 | Human-Centered Design and Usability Testing | 3-0-0-3 | CS305 |
| 6 | CS604 | Distributed Systems | 3-0-0-3 | CS301 |
| 6 | CS605 | Research Project in Computer Science | 3-0-0-3 | - |
| 6 | CS606 | Lab: Mobile Application Development | 0-0-3-1 | CS602 |
| 7 | CS701 | Special Topics in AI and ML | 3-0-0-3 | CS501 |
| 7 | CS702 | Network Security and Cryptography | 3-0-0-3 | CS601 |
| 7 | CS703 | Capstone Project in Computer Science | 3-0-0-3 | - |
| 7 | CS704 | Entrepreneurship and Innovation | 3-0-0-3 | - |
| 7 | CS705 | Advanced Data Science | 3-0-0-3 | CS503 |
| 7 | CS706 | Lab: Capstone Project | 0-0-3-1 | CS703 |
| 8 | CS801 | Thesis and Research Writing | 3-0-0-3 | - |
| 8 | CS802 | Internship | 3-0-0-3 | - |
| 8 | CS803 | Final Year Project | 3-0-0-3 | - |
| 8 | CS804 | Industrial Exposure Program | 3-0-0-3 | - |
| 8 | CS805 | Professional Ethics and Sustainability in Computing | 3-0-0-3 | - |
| 8 | CS806 | Lab: Final Year Project | 0-0-3-1 | CS803 |
Advanced Departmental Electives
The department offers several advanced elective courses that allow students to specialize in specific areas of interest. These courses are designed to provide depth and cutting-edge knowledge in emerging fields of computer science.
Machine Learning and Deep Learning: This course introduces students to neural networks, deep learning architectures, reinforcement learning, and natural language processing. Students gain hands-on experience with frameworks like TensorFlow, PyTorch, and Keras through practical labs and projects.
Cybersecurity Fundamentals: The course covers cryptographic algorithms, secure protocols, penetration testing, and risk management strategies. It prepares students to defend against cyber threats in various domains including financial services, healthcare, and government institutions.
Data Mining and Big Data Analytics: This elective teaches students about data clustering, association rule mining, classification, regression, and time series forecasting. They gain proficiency in tools like Apache Spark, Hadoop, and Scikit-learn, enabling them to analyze large datasets effectively.
Cloud Computing: The course covers cloud architecture models, virtualization technologies, containerization, and service delivery models (IaaS, PaaS, SaaS). Students get exposure to platforms like AWS, Microsoft Azure, and Google Cloud Platform through lab sessions and capstone projects.
Human-Computer Interaction: This course teaches students how to design interfaces that are intuitive, accessible, and user-friendly. Topics include cognitive psychology, usability testing, prototyping tools, and accessibility standards (WCAG).
Internet of Things (IoT): The course explores sensor networks, embedded systems, wireless communication protocols, and smart city applications. Students build IoT devices using Arduino, Raspberry Pi, and NodeMCU platforms.
Advanced Algorithms: This course challenges students to solve complex computational problems using advanced techniques such as dynamic programming, greedy algorithms, graph theory, and approximation algorithms. It is essential for competitive programming and algorithmic interviews at top tech companies.
Software Architecture and Design Patterns: Students are introduced to architectural patterns like MVC, microservices, and event-driven architectures. The course emphasizes best practices in system design, scalability, and maintainability.
Quantum Computing: This elective explores quantum algorithms, qubit manipulation, quantum error correction, and quantum machine learning. With the emergence of quantum computers from companies like IBM, Google, and Rigetti, this course is becoming increasingly relevant.
Research Methodology: The course teaches students how to formulate research questions, conduct literature reviews, design experiments, and write technical reports. This skillset is crucial for pursuing higher education or conducting independent research.
Project-Based Learning Philosophy
At North East Frontier Technical University West Siang, project-based learning is at the heart of our Computer Science program. It is a pedagogical approach that emphasizes experiential learning, critical thinking, and collaborative problem-solving.
The curriculum includes two mandatory mini-projects during the second and fourth semesters. These projects are designed to reinforce theoretical concepts learned in class while allowing students to apply them to real-world scenarios. Mini-project topics range from developing a simple web application to implementing an algorithm for data analysis or creating a mobile app for a specific use case.
The final-year capstone project is the most significant component of our program. Students work individually or in teams on a substantial research or development project under the supervision of faculty mentors. The project must address a relevant challenge within computer science, demonstrating both technical competence and innovation.
Project selection involves a detailed process where students present their interests, research proposals, and feasibility plans. Faculty members guide students through this process, ensuring that each project aligns with their academic goals and industry relevance. The final-year thesis requires students to document their methodology, findings, and conclusions in a comprehensive report.
Throughout the program, students are evaluated based on multiple criteria including technical skills, teamwork, communication abilities, presentation quality, and adherence to deadlines. This holistic assessment approach ensures that graduates are well-rounded professionals capable of thriving in diverse professional environments.