Over the years, Statistics as a subject has shown an immense growth in almost every discipline of Science, Commerce, and Social Science. Recently, many new areas of Statistics are emerging and are showing their significant importance to the age of data analytics such as Big Data and Machine Learning. The classical statistical tools are being modified to form new techniques and methods to deal with the challenges coming from industries like Telecom, Entertainment, Insurance, Banking, Pharmaceutical etc.
By taking the immense need of understanding the data into consideration, the Department of Statistics, under the Sunandan Divatia School of Science, started BSc Applied Statistics and Analytics course in 2015. This course as designed to give the students an insight to applications of Statistics to various fields from the undergraduate level itself. It is very fortunate that this course has got tremendous response from the student fraternity.
Hence, there is a need to take this applied under graduate course to a higher level and introduce the students to more rigorous high performance data mining tools which can enhance their knowledge to apply the statistical techniques to the real world problems. With this objective, the NMIMS (Deemed to be University), under the Sunandan Divatia School of Science, which has always known to be a place to incorporate contemporary changes and flexible in improvising the courses, has introduced M.Sc. Applied Statistics and Analytics programme from academic year 2018-19. This is a more rigorous applied course which focusses on the application of Statistics to almost each and every discipline and is efficient to meet the demands of today’s world be it Big Data, Machine Learning, Data Mining or any other field.
Duration
The rigorous applied course work is spread over 4 semesters, in which the 4 th semester is completely devoted to Industry internship.
Intake
A total of 60 seats are available for the M.Sc. Applied Statistics and Analytics programme.
Eligibility Criterion
Admission Criteria Process
Students who satisfy the requirements of the two stage selection process will be considered for admission to the course
Stage 1 - All eligible candidates will be required to appear for a Written Test to be conducted at the NMIMS campus in Mumbai. The venue will be announced sufficiently in advance of the test date.
Stage 2 - Based on the performance in the written test, candidates will be short listed and called for a personal interview at the NMIMS Campus, Mumbai.
Based on the performance in Stages 1 and 2, a composite merit list will be prepared as per criteria laid down by the University.
BOARD OF STUDIES
Dr. Neetin Desai (Chairman) |
Dean, Sunandan Divatia School of Science, NMIMS |
Dr. M. N. Welling (Co-opted Member) |
Advisor to the President-SVKM & to Chancellor-NMIMS |
Dr. S. D. Varde |
External Advisor, Warwick University |
Dr. T. V. Ramnathan |
Professor & Head, Department of Statistics, Savitribai Phule Pune University |
Mr. Amul Desai |
Director, Myriad Analytics |
Mr. Arnab Das |
Senior Project Manager - IT, HDFC Ergo |
Dr. Sunil Bhardwaj |
Certified Data Scientist & Senior Analytics Consultant - Education, SAS Institute (India) Pvt. Ltd |
Dr. Vinay Kulkarni |
Adjunct Professor, IIT Bombay |
Prof. Sunil Shirvaiker |
Program Director (Statistics), Sunandan Divatia School of Science, NMIMS |
Dr. K S M Rao |
Professor (Statistics), Sunandan Divatia School of Science, NMIMS |
Dr. Pradnya Khandeparkar |
Associate Professor (Statistics), Sunandan Divatia School of Science, NMIMS |
Dr. Leena Kulkarni (Convener) |
Assistant Professor (Statistics), Sunandan Divatia School of Science, NMIMS |
Prof. Prashant Dhamale |
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 |
VALUE PROPOSITION
PROGRAM OBJECTIVES
PEDAGOGY
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 some of the fundamental concepts of statistics in first semester. Subsequently moving to the applied statistical tools in Semester II and introducing the high performance data handling tools in Semester III along with specialized elective disciplines. The fourth semester has completely been devoted to industry internships to give students an exposure to understand the real industry problems. 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 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.
Program outcome
Attendance
The students will be required to have a subject wise minimum attendance of 80%.
Evaluation Criteria
The students will be evaluated through term end exams and through continuous internal assessment. The grade will be awarded at the end of each semester on the basis of Cumulative Grade Point Average.