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Home > Academics > Programs > Bsc-data-science >



Data Science is a recent but a rapidly growing field providing students with exciting career paths, and vertical mobility in education pathways. The B.Sc. program in Data Science gives students a basic foundation in three special, but interrelated, branches of Mathematical Sciences namely, Computer Science, Statistics, and Mathematics. The knowledge of Data Science has not only become inevitable but also relevant for analysing and manipulating voluminous and/or complex data; which in the information era of 21stcentury is a reality of the day. Students of B.Sc. in Data Science program will learn computer programming, data analysis and database systems, and will learn to think critically about the process of handing and understanding data. The B.Sc. in Data Science program is a first-degree program that blends practical use of Data Science methods with the theoretical properties underpinning the performance of the methods and algorithms.

The rigorous course work is spread over 6 semesters including projects

Number of Seats

Mumbai Campus: 40 seats


Candidate must have passed 10 + 2 or equivalent examination including IB Diploma (IB certificate awarded is not eligible) with Mathematics /Mathematics & Statistics/Statistics as compulsory subject & 50% aggregate marks in any stream (Science, Commerce, Arts).

Candidate with IB Diploma is eligible only if he/she has offered Mathematics /Mathematics & Statistics at SL/HL.

Admission Criteria

Merit list will be based on performance of the candidate in Mathematics/ Statistics /Mathematics & Statistics marks obtained in 10+2 or Equivalent examination.

Board of Studies

  • Dr. Sharad Mhaiskar (Special Invitee) – Pro Vice Chancellor, NMIMS Deemed to be University.
  • Prof. Sunil Shirvaiker (Chairman) – Program Director (Statistics), Sunandan Divatia School of Science, NMIMS
  • Prof. P. G. Patki – Vice Principal, Bhavan’s College
  • Dr. Inder K. Rana – Professor, Department of Mathematics, Indian Institute of Technology, Mumbai.
  • Dr. Sushil Kulkarni - Associate Professor of Mathematics, Jai Hind College, Mumba
  • Dr. Siby Abraham - Head, Department of Maths & Stats, Guru Nanak Khalsa College, Matunga, Mumbai
  • Mr. Amul Desai – Director, CoE Analytics & Data Sciences, NMIMS University
  • Dr. K S M Rao - Professor (Statistics), Sunandan Divatia School of Science, NMIMS
  • Dr. Pradnya Khandeparkar – Senior Adjunct Faculty, Sunandan Divatia School of Science, NMIMS
  • Prof. Leena Kulkarni – Assistant Professor (Statistics), Sunandan Divatia School of Science, NMIMS
  • Prof. Shraddha Sarode – Assistant Professor (Computer Science), Sunandan Divatia School of Science, NMIMS
  • Dr. Debasmita Mukherjee – Assistant Professor (Mathematics), Sunandan Divatia School of Science, NMIMS
  • Prof. Prashant Dhamale (Convener) – Assistant Professor (Statistics), Sunandan Divatia School of Science, NMIMS

Salient Features

  • A unique program, designed with inputs from eminent academicians and industry leaders, to focus on building skillsets for the growing requirement of data scientists in the industry.
  • Curriculum focuses on mainly on theoretical as well as practical aspects of Statistics, Computer Science and Mathematics
  • In built opportunity to improve soft skills as well as scientific writing.
  • Grading system at par with international standards.
  • A system of continuous evaluation through seminars, quizzes and practical assignments.
  • Guest faculty drawn from a pool of experts from Industry/academia thereby ensuring a balanced and continuous interaction with the industry.

Program Objectives

  • To expose and provide a strong foundation to the students in the upcoming era of Data Science and Artificial Intelligence.
  • The programme aims at providing a rigorous training in fundamental concepts of Statistics, Mathematics, & Computers Science which creates a strong knowledge base in Data Science domain.
  • To provide a complete understanding of the subject by introducing projects from the third semester on the relevant subject.
  • Focus on blending theory with practical and industry application to enhance understanding and learning.
  • Focus on the overall development of the students to help gain knowledge and skillsets required for further studies after completion of the course.


The course lays emphasis on the overall development of computational and analytical skills of a student coupled with an expansion of his/her knowledge base through an interdisciplinary course. The course comprises of lectures and practical on the basic concepts of Statistics, Mathematics, and Computer Science in the first year. Subsequently moving to the second year, the students are exposed to the core subjects of Statistics and Mathematics. From the third semester student has to do a project in any of the core subject taught in that semester. In the fifth semester, students will be exposed to the papers such Machine Learning techniques. In final semester subject of Deep learning techniques other statistical papers will make student ready to pursue further study in the field of Data Science.

The course is designed in consultation with our Board of Studies, which comprises of experts from academia, research institutions and industry. Thus, the course is tailor made to fulfill the requirements needed to keep pace with the current & future developments in industry.

While the student will have ample opportunity to acquire hands-on training on modern softwares wherever necessary, he/she will also be able to benefit from the expertise of one or more supervisors, wherever needed.

Along with the permanent faculties, the regular lectures are also conducted by visiting faculties who are experts in their respective fields. Apart from the course work, the Faculty also conducts Guest lectures by eminent academicians and statisticians to ensure learner centric environment.

Value Proposition

·Aims to provide a strong foundation for the student in the field of Data Science

·Rigorous training on the foundational subjects of Statistics, Mathematics, Computer Science and Deep learning

·Experiential hands on training on a host of critical tools and technologies related to Data Science

·Early initiation of students to research oriented projects for gaining better understanding of the subjects

Course Curriculum

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