B.E. Computer Science and
Engineering (Data Science)

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Curriculum
  • The B.E. in Computer Science and Engineering (Data Science) provides a strong foundation in Data Science, Artificial Intelligence, Machine Learning, Statistics, and Computing, enabling students to build analytical, problem-solving, and decision-making skills essential for data-driven careers. The curriculum combines core computer science principles with specialized data science courses to prepare students for emerging roles in AI, analytics, and intelligent systems. Major Honours courses offer advanced specialization, while Minor Degree courses allow students to explore interdisciplinary domains, enhancing their knowledge and career opportunities.
  • The curriculum is comprehensively designed to remain current and industry-relevant, with revisions undertaken every four years and, from 2025 onwards, updated annually to align with rapid technological advancements. Developed through inputs from industry experts and academia, the curriculum covers emerging areas such as Data Science, Machine Learning, Deep Learning, Artificial Intelligence, Big Data Analytics, Data Visualization, Data Mining, Natural Language Processing, Computer Vision, Generative AI, Large Language Models (LLMs), Reinforcement Learning, MLOps, and Cloud Computing. Innovative teaching methodologies, including flipped classrooms, project-based learning, activity-based learning, case studies, seminars, workshops, and hands-on laboratory sessions, provide students with experiential learning opportunities. The curriculum follows a Choice Based Credit System (CBCS) with a total of 160 credits.
curriculum comp science engg
  • The curriculum offers professional elective courses in advanced domains such as Generative AI and LLMs, Computer Vision, Deep Learning, Natural Language Processing, MLOps, Information and Network Security, Cyber Security, DevOps, Internet of Things, Distributed Systems, Blockchain Technology, Mobile Application Development, Robotic Process Automation, and Cloud Computing. Open elective courses provide students with opportunities to strengthen their knowledge in core computing concepts and interdisciplinary technologies.
    Students develop industry-ready competencies through extensive hands-on learning in Python Programming, Data Analytics, Machine Learning, Deep Learning, Big Data Analytics, Data Visualization, Database Management Systems, Cloud Computing, Artificial Intelligence, and Full Stack Development. This practical exposure enables students to collect, process, analyze, and visualize large-scale data, build intelligent predictive models, and develop scalable, data-driven applications for real-world challenges.
  • The curriculum is designed through continuous feedback from faculty, students, parents, alumni, industry professionals, and academic experts, ensuring alignment with evolving industry requirements and global technology trends.
  • To strengthen industry exposure, the curriculum provides flexible internship opportunities through Swappable Semester and Two-Semester Internship schemes, enabling students to undertake long-term industrial internships without affecting academic progress.
    In addition to the academic curriculum, students can enhance their professional skills through Ability Enhancement Courses (AEC), Professional Ethics, Universal Human Values, Indian Knowledge System, and Biology for Engineers. Students also gain practical exposure through specialized laboratories, technical workshops, hackathons, certification programs, and industry interactions that foster innovation, teamwork, and product development skills.
  • Projects undertaken throughout the program encourage students to apply Data Science and Artificial Intelligence techniques to solve real-world industrial and societal problems, promoting innovation, research aptitude, and entrepreneurial thinking.
First Year

Undergraduate

2022

2021

2020

Undergraduate

2022

2021

2020

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