Comprehensive Course Structure
The Computer Science curriculum at Martin Luther Christian University Shillong is designed to provide students with a balanced blend of theoretical knowledge and practical application. The program spans eight semesters, with each semester offering a carefully curated set of core courses, departmental electives, science electives, and laboratory sessions.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | CS101 | Introduction to Programming | 3-0-0-3 | - |
| I | CS102 | Mathematics for Computer Science I | 3-0-0-3 | - |
| I | CS103 | Computer Organization and Architecture | 3-0-0-3 | - |
| I | CS104 | Introduction to Data Structures and Algorithms | 3-0-0-3 | - |
| I | CS105 | Physics for Computer Science | 3-0-0-3 | - |
| I | CS106 | English Communication Skills | 2-0-0-2 | - |
| I | CS107 | Introduction to Laboratory | 0-0-3-1 | - |
| II | CS201 | Object-Oriented Programming with Java | 3-0-0-3 | CS101 |
| II | CS202 | Mathematics for Computer Science II | 3-0-0-3 | CS102 |
| II | CS203 | Digital Logic and Microprocessor | 3-0-0-3 | CS103 |
| II | CS204 | Database Management Systems | 3-0-0-3 | CS104 |
| II | CS205 | Probability and Statistics | 3-0-0-3 | CS102 |
| II | CS206 | Professional Communication Skills | 2-0-0-2 | - |
| II | CS207 | Programming Laboratory | 0-0-3-1 | CS101 |
| III | CS301 | Operating Systems | 3-0-0-3 | CS201, CS203 |
| III | CS302 | Computer Networks | 3-0-0-3 | CS204 |
| III | CS303 | Software Engineering | 3-0-0-3 | CS201 |
| III | CS304 | Data Structures and Algorithms II | 3-0-0-3 | CS104 |
| III | CS305 | Linear Algebra and Numerical Methods | 3-0-0-3 | CS102 |
| III | CS306 | Design Thinking for Technology | 2-0-0-2 | - |
| III | CS307 | Systems Programming Laboratory | 0-0-3-1 | CS201, CS203 |
| IV | CS401 | Machine Learning Fundamentals | 3-0-0-3 | CS304, CS305 |
| IV | CS402 | Cryptography and Network Security | 3-0-0-3 | CS204 |
| IV | CS403 | Web Technologies and Development | 3-0-0-3 | CS201, CS204 |
| IV | CS404 | Artificial Intelligence | 3-0-0-3 | CS301, CS304 |
| IV | CS405 | Data Mining and Analytics | 3-0-0-3 | CS205, CS304 |
| IV | CS406 | Innovation and Entrepreneurship | 2-0-0-2 | - |
| IV | CS407 | Advanced Laboratory Project | 0-0-3-1 | CS301, CS304 |
| V | CS501 | Advanced Algorithms | 3-0-0-3 | CS304 |
| V | CS502 | Distributed Systems | 3-0-0-3 | CS301, CS302 |
| V | CS503 | Cloud Computing | 3-0-0-3 | CS301, CS302 |
| V | CS504 | Human-Computer Interaction | 3-0-0-3 | CS303 |
| V | CS505 | Database Design and Management | 3-0-0-3 | CS204 |
| V | CS506 | Research Methodology | 2-0-0-2 | - |
| V | CS507 | Capstone Project I | 0-0-3-1 | - |
| VI | CS601 | Advanced Machine Learning | 3-0-0-3 | CS401 |
| VI | CS602 | Security Architecture and Policy | 3-0-0-3 | CS402 |
| VI | CS603 | Mobile Application Development | 3-0-0-3 | CS303, CS403 |
| VI | CS604 | Natural Language Processing | 3-0-0-3 | CS401 |
| VI | CS605 | Big Data Technologies | 3-0-0-3 | CS405 |
| VI | CS606 | Internship Program | 0-0-0-2 | - |
| VI | CS607 | Capstone Project II | 0-0-3-1 | CS507 |
| VII | CS701 | Specialized Topics in AI | 3-0-0-3 | CS401, CS601 |
| VII | CS702 | Cybersecurity Research | 3-0-0-3 | CS402, CS602 |
| VII | CS703 | Embedded Systems Design | 3-0-0-3 | CS301, CS203 |
| VII | CS704 | Computational Biology | 3-0-0-3 | CS305, CS405 |
| VII | CS705 | Financial Technology (FinTech) | 3-0-0-3 | CS305, CS405 |
| VII | CS706 | Research Internship | 0-0-0-2 | - |
| VII | CS707 | Capstone Project III | 0-0-3-1 | CS607 |
| VIII | CS801 | Thesis Proposal and Supervision | 0-0-0-4 | - |
| VIII | CS802 | Final Year Project | 0-0-3-4 | CS707 |
| VIII | CS803 | Industry Interaction Workshop | 0-0-2-1 | - |
| VIII | CS804 | Final Evaluation and Presentation | 0-0-0-1 | CS802 |
| VIII | CS805 | Professional Ethics in Technology | 2-0-0-2 | - |
Advanced Departmental Electives
The department offers a wide range of advanced departmental electives that allow students to explore specialized areas of interest and build depth in their chosen field. These courses are taught by leading faculty members and are aligned with current industry trends and research advancements.
Advanced Machine Learning (CS601)
This course delves into advanced topics in machine learning, including reinforcement learning, deep generative models, neural architecture search, and multi-agent systems. Students learn to design and implement complex learning algorithms using frameworks like TensorFlow and PyTorch. The course includes both theoretical components and practical projects that involve real-world datasets and applications.
Cybersecurity Research (CS702)
This elective explores the latest developments in cybersecurity, focusing on emerging threats, cryptographic protocols, and secure system design. Students engage in research projects related to blockchain security, cloud security, and privacy-preserving computation. The course emphasizes hands-on experimentation with industry-standard tools and platforms.
Embedded Systems Design (CS703)
This course provides students with an in-depth understanding of embedded systems architecture and design principles. Topics include real-time operating systems, microcontroller programming, sensor integration, and IoT applications. Students work on projects involving hardware-software co-design and develop prototypes for various industrial and consumer applications.
Computational Biology (CS704)
This interdisciplinary course combines computer science with biology to solve complex problems in genomics, proteomics, and systems biology. Students learn to apply computational methods such as sequence alignment, phylogenetic analysis, and protein structure prediction. The course includes practical sessions on bioinformatics tools and databases.
Financial Technology (FinTech) (CS705)
This elective introduces students to the intersection of finance and technology, focusing on digital payment systems, algorithmic trading, risk management, and regulatory compliance. Students explore the use of blockchain, AI, and data analytics in financial services. Projects include developing fintech applications and analyzing financial datasets.
Project-Based Learning Philosophy
The Computer Science department at Martin Luther Christian University Shillong strongly believes in project-based learning as a cornerstone of effective education. This approach emphasizes experiential learning, where students actively engage in solving real-world problems through structured projects.
The program includes mandatory mini-projects throughout the curriculum, starting from the first year and culminating in the final-year thesis. These projects are designed to reinforce theoretical concepts learned in class and provide students with practical experience in software development, research, and problem-solving.
Mini-projects are typically completed in teams of 3-5 students and involve selecting a relevant topic within their area of interest. Students work under the guidance of faculty mentors who provide technical support and feedback throughout the project lifecycle. The projects are evaluated based on criteria such as technical implementation, innovation, documentation quality, and presentation skills.
The final-year capstone project represents the culmination of the student's academic journey. It involves conducting original research or developing a comprehensive software solution that addresses a significant challenge in the field. Students are paired with faculty mentors who guide them through the process of defining objectives, designing solutions, implementing prototypes, and presenting findings to a panel of experts.
Project selection is facilitated through a structured process that includes topic brainstorming sessions, proposal submissions, and mentor allocation based on expertise alignment. This ensures that students are exposed to diverse perspectives and gain exposure to cutting-edge technologies and methodologies.