PO1: Critical Thinking: Apply knowledge of Computer Science to identify, analyse problems and to provide effective solution in the area of Computing.
PO2: Computing Skills and Ethics: Analyse a problem, and identify and define the computing requirements appropriate to its solution.
PO3: Analytical skill: Ability to design, develop algorithms and provide software solutions to cater the industrial needs.
PO4: Modern Tool Usage: Use current techniques, skills, and tools necessary for computing practices
PO5: Employability Skills: Inculcate skills to excel in the fields of Information Technology and its Enabled services, Government and Private sectors, Teaching and Research.
PO6: Ethics: Insists ethical responsibilities, human and professional values and make their contribution to the society.
PO7: Self Directed and Life-long Learning: Engaged in lifelong learning to equip them to changing environment and be prepared to take-up mastering programmes.
PO8: Individual and team work: Function effectively as an individual, and as a member or a leader in diverse team and multidisciplinary settings.
PO9: 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.
PO10: Project management and finance: Demonstrate knowledge and understanding of the problem and management principles and apply these to one’s own work, as a member and engineering and   management principles and apply these to one’s own work, as a member.
PO11: 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.
PO12: 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.

CURRICULUM & SYLLABUS
MINIMUM CREDITS TO BE EARNED: 90

Code No	Course			Hours/Week			Maximum Marks
		Lecture	Tutorial	Practical	Credits	CA	SEE	SEE
Core	Fundamentals of Data Science	4	0	0	4	40	60	100
Core	Java & Data Structures	4	0	0	4	40	60	100
Core	Advanced DBMS	3	0	0	3	40	60	100
Core – Practical	Data Structures using Java Lab	0	0	4	2	40	60	100
Core – Practical	RDBMS Lab	0	0	4	2	40	60	100
DSE	DSE 1	3	0	0	3	40	60	100
DSE	DSE 2	3	0	0	3	40	60	100
SEC	Soft Skill 1	2	0	0	2	40	60	100
		19	0	8	23

View full course curriculum

Program	Years	Eligibility	Criteria for Merit
M.Sc (Data Science & Business Analytics)	2 Yrs (4 Semester)	Bachelor degree in Computer Science/Computer Applications/Information Technology/ Any other equivalent degree in Information Technology and Computer Science (or) B.Sc in Physics/Mathematics/Statistics/BBA/B.Com/B.Com with any specialization	Merit based on percentage of marks secured in the qualifying examination

Tuition Fee 2023 - 2024 (Per Sem)	Other Fee (Per Sem)	Total Fee (Per Sem)
30,000	10,000	40,000