Curriculum Overview
The Computer Applications program at University Of Science And Technology Meghalaya is structured over 8 semesters, with a carefully designed curriculum that balances theoretical knowledge with practical application. The program includes core courses, departmental electives, science electives, and laboratory sessions to provide students with a comprehensive understanding of the field.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming | 3-0-0-3 | - |
| 1 | CS102 | Mathematics for Computing | 3-0-0-3 | - |
| 1 | CS103 | Computer Organization | 3-0-0-3 | - |
| 1 | CS104 | Engineering Graphics | 2-0-0-2 | - |
| 1 | CS105 | Communication Skills | 2-0-0-2 | - |
| 1 | CS106 | Introduction to Algorithms | 3-0-0-3 | - |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 2 | CS202 | Database Management Systems | 3-0-0-3 | CS101 |
| 2 | CS203 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| 2 | CS204 | Operating Systems | 3-0-0-3 | CS103 |
| 2 | CS205 | Computer Networks | 3-0-0-3 | CS103 |
| 2 | CS206 | Web Technologies | 3-0-0-3 | CS101 |
| 3 | CS301 | Machine Learning | 3-0-0-3 | CS201 |
| 3 | CS302 | Cybersecurity | 3-0-0-3 | CS205 |
| 3 | CS303 | Data Analytics | 3-0-0-3 | CS201 |
| 3 | CS304 | Software Engineering | 3-0-0-3 | CS203 |
| 3 | CS305 | Mobile App Development | 3-0-0-3 | CS203 |
| 3 | CS306 | Embedded Systems | 3-0-0-3 | CS103 |
| 4 | CS401 | Advanced Machine Learning | 3-0-0-3 | CS301 |
| 4 | CS402 | Cloud Computing | 3-0-0-3 | CS205 |
| 4 | CS403 | Human-Computer Interaction | 3-0-0-3 | CS203 |
| 4 | CS404 | Internet of Things | 3-0-0-3 | CS306 |
| 4 | CS405 | Computational Biology | 3-0-0-3 | CS201 |
| 4 | CS406 | Game Development | 3-0-0-3 | CS203 |
| 5 | CS501 | Research Methodology | 3-0-0-3 | - |
| 5 | CS502 | Advanced Data Science | 3-0-0-3 | CS303 |
| 5 | CS503 | Network Security | 3-0-0-3 | CS205 |
| 5 | CS504 | Software Architecture | 3-0-0-3 | CS204 |
| 5 | CS505 | Mobile Application Design | 3-0-0-3 | CS305 |
| 5 | CS506 | DevOps Practices | 3-0-0-3 | CS204 |
| 6 | CS601 | Capstone Project | 3-0-0-3 | CS501 |
| 6 | CS602 | Specialized Elective I | 3-0-0-3 | - |
| 6 | CS603 | Specialized Elective II | 3-0-0-3 | - |
| 6 | CS604 | Specialized Elective III | 3-0-0-3 | - |
| 6 | CS605 | Specialized Elective IV | 3-0-0-3 | - |
| 6 | CS606 | Internship | 3-0-0-3 | - |
| 7 | CS701 | Advanced Topics in AI | 3-0-0-3 | CS301 |
| 7 | CS702 | Advanced Cybersecurity | 3-0-0-3 | CS302 |
| 7 | CS703 | Big Data Analytics | 3-0-0-3 | CS303 |
| 7 | CS704 | Cloud Architecture | 3-0-0-3 | CS402 |
| 7 | CS705 | UX Design | 3-0-0-3 | CS304 |
| 7 | CS706 | IoT Applications | 3-0-0-3 | CS404 |
| 8 | CS801 | Final Year Project | 3-0-0-3 | CS601 |
| 8 | CS802 | Specialized Elective V | 3-0-0-3 | - |
| 8 | CS803 | Specialized Elective VI | 3-0-0-3 | - |
| 8 | CS804 | Specialized Elective VII | 3-0-0-3 | - |
| 8 | CS805 | Specialized Elective VIII | 3-0-0-3 | - |
| 8 | CS806 | Research Thesis | 3-0-0-3 | CS501 |
Advanced Departmental Elective Courses
The department offers a range of advanced elective courses that allow students to specialize in areas of interest and gain in-depth knowledge. These courses are designed to provide students with the latest industry practices and research insights.
Advanced Machine Learning
This course delves into advanced topics in machine learning, including reinforcement learning, deep learning architectures, and neural network optimization. Students will explore real-world applications and develop models for complex datasets.
Cloud Computing
This course covers cloud computing fundamentals, including virtualization, distributed systems, and cloud service models. Students will gain hands-on experience with platforms like AWS, Azure, and Google Cloud.
Human-Computer Interaction
This course explores the design and evaluation of user interfaces, focusing on usability principles and interaction design. Students will learn about user research, prototyping, and usability testing.
Internet of Things
This course introduces students to IoT technologies, including sensors, actuators, and communication protocols. Students will develop IoT applications and learn about edge computing and data processing.
Computational Biology
This course combines computer science and biology to solve complex biological problems. Students will learn about genomics, proteomics, and computational modeling.
Game Development
This course focuses on the development of interactive multimedia content, including game engines, 3D modeling, and animation. Students will learn about game design principles and development tools.
Advanced Data Science
This course covers advanced statistical methods, data visualization, and predictive modeling. Students will work with large datasets and develop models for business intelligence.
Network Security
This course explores network security threats and defense mechanisms. Students will learn about cryptography, firewalls, and intrusion detection systems.
Software Architecture
This course focuses on the design and implementation of scalable software systems. Students will learn about architecture patterns, design principles, and software development methodologies.
Mobile Application Design
This course covers the design and development of mobile applications for iOS and Android platforms. Students will learn about UI/UX design, app architecture, and deployment.
Project-Based Learning Philosophy
The department strongly emphasizes project-based learning as a core component of the curriculum. This approach ensures that students apply theoretical knowledge to real-world challenges and develop practical skills.
Mini-projects are introduced in the third and fourth semesters, where students work in teams to solve specific problems. These projects are evaluated based on technical execution, innovation, and presentation skills.
The final-year thesis or capstone project is a comprehensive endeavor that integrates all the knowledge and skills acquired throughout the program. Students work closely with faculty mentors to develop innovative solutions, often collaborating with industry partners.
Students select their projects based on their interests and career goals, with faculty mentors guiding them through the process. The project selection process involves a proposal submission, mentor assignment, and regular progress reviews.
The evaluation criteria for projects include technical depth, creativity, presentation, and documentation. Students are encouraged to present their work at conferences and competitions, further enhancing their professional development.