Department of Computer Science and Engineering (Data Science)

About Department

Data Science has emerged as one of the most transformative disciplines in the digital era, driven by the exponential growth of data generated across industries, governments, and society. Studying Data Science at the undergraduate level builds a strong foundation in programming, mathematical reasoning, and analytical thinking at an early stage, enabling students to derive meaningful insights from complex and large-scale data.

The Computer Science and Engineering (Data Science) programme was started in the year 2025 with an intake of 60 students. The programme focuses on transforming data into actionable intelligence through strong foundations in statistics, machine learning, artificial intelligence, and computational thinking. It emphasizes hands-on learning, interdisciplinary research, and real-world problem solving to address challenges across domains such as healthcare, finance, retail, smart cities, and social analytics.

The curriculum follows the principles of Outcome-Based Education (OBE) and integrates theory with extensive laboratory work, mini-projects, case studies, internships, and capstone projects. Students gain exposure to modern programming ecosystems, open-source tools, data engineering platforms, and cloud-based data analytics frameworks. Innovative teaching–learning practices and continuous assessment methods are adopted to enhance analytical thinking, creativity, and problem-solving skills.

The programme aims to nurture industry-ready professionals, entrepreneurs, and researchers capable of driving innovation and data-driven decision-making in a globally competitive environment, while upholding ethical values and social responsibility.

Vision

To be a center of excellence in Computer Science and Engineering (Data Science) through quality education, impactful research, and innovation, addressing industry needs and societal challenges responsibly.

Mission

• To impart strong foundational knowledge in computer science and data science through a contemporary curriculum that integrates theory, practical skills, and emerging technologies.
• To develop competent and innovative professionals by fostering analytical thinking, research orientation, industry collaboration, and hands-on experience in data analytics, machine learning, and artificial intelligence.
• To nurture ethical, socially responsible, and lifelong learners capable of applying data-driven solutions to real-world problems for the benefit of industry and society.