Dept. of CSE (Data Science)

Department Profile

Computer Science & Engineering (Data Science) department came into existence from the academic year 2021-22. Salient features of the department are as follow:

Architecture and curriculum has been designed by a team of experienced faculty, data scientists and industry subject matter experts.
Through collaborations, internships, classroom teaching, and hands-on experience, students shall immerse themselves in the fields of technology, business, and communications and build a comprehensive skill set in Data Science.
Core competencies in multiple areas - Programming, Mathematics, Statistics, Data Analytics, Artificial Intelligence, Machine Learning, Internet of Things, Data Wrangling, Data Visualization, Communication, Business Foundations, and Ethics will increase employability in the fast-paced Data Science industry.

The department has well established laboratories, resourceful faculty and staff. It is noteworthy that the faculty are well versed in both teaching and research.

HoDs Desk

Welcome to the age of data - where a need exists for a new class of experts who can extract actionable knowledge from rich and varied datasets.

Every day, huge amounts of data are generated by business, scientific, and social activity taking place all around us. With data coming from sensors, digital images, streaming video, satellite and medical imagery, and from interactions with cloud computing, data-driven approaches to decision making are being applied in areas as diverse as medicine, business, advertising, and entertainment.

The Computer Science & Engineering (Data Science) is a rigorous program that will provide students with a foundation in those aspects of computer science, statistics, and mathematics that are relevant for analyzing and manipulating large complex datasets. Students will be exposed to both the practical use of data science methods as well as the theoretical properties underpinning the performance of the methods and algorithms. Graduates of the program will be well prepared for exciting careers in data science and will have opportunities for advanced study.

VISION & MISSION

VISION

Prepares the next generation practitioners to transform a world of data into a world of intelligence.

MISSION

Through our educational program, we address the analytical and data-centric needs of a modern workforce to empower and inspire.
Instill highest ethical standards, social responsibility and values with a sense of professionalism.
Fostering team spirit for pursuing inter-disciplinary research among the faculty and the students to create state of art research facilities.
Building trusted relationship with industry

Programme Educational Objectives (PEOs)

PEO1	Establish themselves in various technical roles by solving real world problems using core topics in Computer Science with emphasis on Data science.
PEO2	Develop professional skills that equip them for employment and for higher education in contemporary areas in Data Science.
PEO3	Apply research and entrepreneurial skills augmented with a rich set of communication, teamwork and leadership skills to excel in their profession.

Programme Outcomes (POs)

PO1	Engineering knowledge: Apply knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO2	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.
PO3	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.
PO4	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.
PO5	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.
PO6	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.
PO7	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.
PO8	Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO9	Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO10	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.
PO11	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.
PO12	Life-long learning: Recognize the need for, and have preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Programme Specific Outcomes (PSOs)

PSO1	Ability to solve contemporary problems in Computer Science by applying Data science principles, including Machine Learning, Cloud Computing, Internet of Things and Data Analytics.
PSO2	Ability to apply technical skills learnt through professional society events, certification programs, projects and/or lab exercise to provide sustainable solutions to Computer science and Data science related to society and environment.
PSO3	Ability to practice as an ethical software engineer/researcher in the evolving discipline of Computer Science by employing Data Science skills learnt through internships and collaborative projects with industry.