Programme Details

UG: Under graduate program

  • B.Tech Computer Science & Engineering(Data Science)
  • Year of Commencement: 2020-21
  • Intake : 60 increase to 180 in year(2023-2024)


Prof. Aarti Karandikar (HOD)

Vision :

To continually improve the education environment, in order to develop graduates with strong academic and technical background needed to achieve distinction in the discipline. Excellence is expected in various domains like workforce, higher studies or lifelong learning. To strengthen links between industry through partnership and collaborative development works.

Mission :

To develop a strong foundation of theory and practices of computer science amongst the students to enable them to develop into knowledgeable, responsible professionals, lifelong learners and implement the latest computing technologies for the betterment of the society.

Programme Outcomes of Computer Science & Engineering are:

  • Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  • Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  • Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  • Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
  • The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  • Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  • Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  • Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  • Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change.


  • Graduates will have a strong foundation of knowledge and skills in mathematics, statistics,programming and computer science to solve problems in data science.
  • Graduates will have the ability and attitude to adapt to emerging technological changes with life long learning skills.
  • Graduates will demonstrate collaborative learning and spirit of team work through multidisciplinary Data Science projects ensure ethical and moral values.
  • Graduates will demonstrate professionalism, ethical attitude, teamwork and leadership skills with lifelong learning in the career.


PSO-I) Apply the concepts and practical knowledge of data science in analysis, design and development of computing systems and applications to multi-disciplinary problems.

PSO-II) Acquaint with the contemporary trends in industrial/research settings and thereby innovate novel solutions to existing problems.