B.Sc. (Applied Statistics & Analytics)

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.

Duration: 

4-year Bachelor of Science Degree in Applied Statistics & Analytics with options to exit in the foundation, diploma or B.Sc. degree level.

Number of Seats

• Mumbai Campus – 60 seats

Eligibility:

Candidate must have passed 10 + 2 or equivalent examination from recognized board with Mathematics/ Mathematics & Statistics as compulsory subject with minimum 50% aggregate marks in any stream (Science/Commerce/Arts with Mathematics/ Mathematics & Statistics).

Admission Criteria:

• Merit list will be based on the performance of the candidates in NMIMS-MST
• The scores of NMIMS-MST will be considered for the merit list process.
• The decision of the institute will be final in this regard and no inquiries or correspondence in this regard will be entertained

 

Value Proposition

• 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 applied as well as theoretical aspects of Statistics alongwith subjects from Economics, Mathematics, Computers & Analytics.
• Extensive use of the following soft wares MS Excel, R Studio, Python, SQL, Oracle, SAS Visual Analytics to solve practical problems and projects.
• 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 students to the upcoming era of Machine Learning & Data Science
• The programme aims at providing a rigorous training in fundamental concepts of Statistics, Mathematics, Economics & Computers 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 statistical subject.
• Introduce two core business areas i.e. Marketing Analytics and Financial Risk Analytics to give a deeper insight of the business domain at the undergraduate level
• 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 as well as for an edge in employability after completion of the course.

 

 

 

 

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 the basic concepts of Statistics, Mathematics, Economics and Computer Programming in the first year. Subsequently moving to the second year, the students are exposed to the core subjects of Statistics along with some papers of Economics and Mathematics. From the third semester student has to do a project in any of the core statistical subject taught in that semester. In the fifth year, students will be exposed to the fundamental papers of Marketing analytics and Financial Risk analytics domain along with the core statistical subjects. Project has to be done in any one of the core statistical paper. In final semester subject of Data Science is introduced with statistical modelling papers of the Marketing Analytics and Risk Analytics. Students are supposed to do a project in 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.

Salient Features

• Curriculum prepared with inputs from eminent academicians and industry leaders, to focus on building skillsets for the growing requirement of data scientists in the industry
• Applied Statistics and Analytics form the core of the curriculum
• Curriculum contains components from Statistics, Economics, Mathematics, Computers and Analytics and emphasis on Experiential learning
• Focused on blending theory with practical and industry application to enhance understanding and learning.
• Hands on experience on using software like MS Excel, RStudio, C++, SQL, Oracle, Scilab, SPSS, SAS Visual Analytics, to solve problems involving analytics
• Regular interaction with Industry leaders to give a holistic picture of importance and application of Analytics in the industry
• Industry projects are part of the curriculum
• Faculty are drawn from a pool of experts from Industry/academia thereby ensuring a balanced and continuous interaction with the industry

PROGRAM OUTCOME

---

Program structure as per NEP from A.Y. 2024-2025 onwards

---

Program Structure for Batch 2023-2026