Comprehensive Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | LAR101 | Introduction to Liberal Arts | 3-0-0-3 | - |
| 1 | LAR102 | English Composition | 3-0-0-3 | - |
| 1 | MAT101 | Calculus I | 4-0-0-4 | - |
| 1 | PHY101 | Physics Fundamentals | 3-0-0-3 | - |
| 2 | LAR201 | Philosophy of Knowledge | 3-0-0-3 | LAR101 |
| 2 | MAT201 | Statistics for Social Sciences | 3-0-0-3 | MAT101 |
| 2 | HIS201 | History of Ideas | 3-0-0-3 | - |
| 2 | CSC201 | Introduction to Programming | 3-0-0-3 | - |
| 3 | LAR301 | Human Rights and Ethics | 3-0-0-3 | LAR201 |
| 3 | SOC301 | Sociology of Technology | 3-0-0-3 | - |
| 3 | ECS301 | Economics for Social Sciences | 3-0-0-3 | MAT201 |
| 3 | PSY301 | Psychology of Decision Making | 3-0-0-3 | - |
| 4 | LAR401 | Global Media and Communication | 3-0-0-3 | - |
| 4 | CSC401 | Data Science Fundamentals | 3-0-0-3 | CSC201 |
| 4 | ENG401 | Advanced English Literature | 3-0-0-3 | LAR102 |
| 4 | MAT401 | Mathematical Modeling | 3-0-0-3 | MAT201 |
| 5 | LAR501 | Public Policy Analysis | 3-0-0-3 | ECS301 |
| 5 | INT501 | International Relations Theory | 3-0-0-3 | - |
| 5 | CSC501 | Machine Learning Applications | 3-0-0-3 | CSC401 |
| 5 | HIS501 | Modern History of India | 3-0-0-3 | HIS201 |
| 6 | LAR601 | Capstone Project in Liberal Arts | 4-0-0-4 | - |
| 6 | CSC601 | Research Ethics and Data Privacy | 3-0-0-3 | - |
| 6 | SOC601 | Social Innovation and Entrepreneurship | 3-0-0-3 | SOC301 |
| 6 | MAT601 | Advanced Mathematical Methods | 3-0-0-3 | MAT401 |
| 7 | LAR701 | Digital Humanities and Archives | 3-0-0-3 | - |
| 7 | CSC701 | Advanced Data Visualization | 3-0-0-3 | CSC501 |
| 7 | PSY701 | Cognitive Psychology and AI | 3-0-0-3 | PSY301 |
| 7 | HIS701 | Colonialism and Postcolonial Studies | 3-0-0-3 | HIS501 |
| 8 | LAR801 | Thesis Writing and Publication | 4-0-0-4 | - |
| 8 | CSC801 | Capstone Research in AI | 3-0-0-3 | CSC701 |
| 8 | SOC801 | Community Engagement and Advocacy | 3-0-0-3 | - |
| 8 | MAT801 | Mathematical Modeling in Social Sciences | 3-0-0-3 | MAT601 |
Advanced Departmental Elective Courses
Philosophy of Knowledge (LAR301): This course explores fundamental questions about the nature of knowledge, truth, belief, and justification. Students examine major philosophical schools of thought including empiricism, rationalism, pragmatism, and postmodernism. The course emphasizes critical thinking skills and encourages students to engage with contemporary debates in epistemology.
Global Media and Communication (LAR401): This elective delves into the role of media in shaping public opinion, culture, and politics across different societies. Students analyze global media systems, digital communication platforms, and their impact on democracy, identity formation, and social movements.
Data Science Fundamentals (CSC401): Designed for students with no prior programming background, this course introduces basic concepts of data analysis using Python and SQL. Topics include descriptive statistics, data visualization, hypothesis testing, regression modeling, and ethical considerations in data science.
Social Innovation and Entrepreneurship (SOC601): This course focuses on how social enterprises can address pressing societal issues through innovative business models. Students learn about impact measurement frameworks, sustainable development goals, and practical tools for launching scalable initiatives that create positive change.
Advanced Data Visualization (CSC701): Building upon earlier data science courses, this course teaches students to communicate complex findings effectively through interactive dashboards, infographics, and narrative storytelling techniques. Students work with advanced visualization software such as Tableau, Power BI, and D3.js.
Cognitive Psychology and AI (PSY701): This interdisciplinary course bridges psychology and artificial intelligence by examining how human cognition mirrors machine learning algorithms. Students study topics such as neural networks, decision-making processes, attention mechanisms, and cognitive biases in AI systems.
Colonialism and Postcolonial Studies (HIS701): This advanced course investigates the historical roots of colonialism and its lasting effects on contemporary global inequalities. Students explore literary works, political theories, and cultural artifacts from colonized regions to understand resistance movements and decolonization efforts.
Machine Learning Applications (CSC501): This elective introduces students to supervised and unsupervised learning techniques used in real-world applications. Through hands-on projects, students gain experience implementing algorithms in areas such as natural language processing, image recognition, and recommendation systems.
Digital Humanities and Archives (LAR701): Students learn how digital technologies can be applied to preserve and interpret historical documents, manuscripts, and cultural artifacts. This course combines traditional humanities methodologies with computational tools for text mining, digital mapping, and multimedia presentation.
Research Ethics and Data Privacy (CSC601): As data becomes increasingly valuable, this course addresses ethical dilemmas in research practices involving personal information and algorithmic bias. Students examine case studies from academia, industry, and government to develop a framework for responsible data stewardship.
Mathematical Modeling in Social Sciences (MAT801): Using mathematical tools, students learn to model social phenomena such as population dynamics, voting behavior, and economic trends. This course integrates differential equations, probability theory, and statistical inference to explain observed patterns in human societies.
Thesis Writing and Publication (LAR801): The capstone course guides students through the process of writing a substantial academic thesis. From topic selection and literature review to methodology design and final publication, students receive individual mentorship and feedback from faculty advisors.
Project-Based Learning Philosophy
The Liberal Arts program places great emphasis on project-based learning as a means of fostering creativity, collaboration, and critical thinking. Students are encouraged to pursue independent projects that connect their academic interests with real-world challenges.
Mini-projects, typically completed during the second and third years, allow students to apply theoretical concepts in practical contexts. These projects often involve working in teams to solve problems posed by local organizations or international NGOs.
The final-year thesis/capstone project is a significant undertaking that requires students to conduct original research on a topic of their choosing. Students select mentors from the faculty based on shared interests and collaborate closely throughout the research process. The project culminates in a written thesis, an oral presentation, and a public defense before a panel of experts.
Project selection is guided by student preferences, faculty availability, and alignment with current research priorities. Each student works under the supervision of a dedicated faculty mentor who provides guidance on methodology, resources, and timelines.