MS Business Analytics

Introduction

Mission Statement:

To enable the participants to develop capabilities for highly sophisticated and complex decisions making by proficiently applying analytical theories and articulating processes for both organizations at the local and global level.

Rationale:

Given the massive data being generated (Big Data) in the present environment defined by rapid diffusion of information technology, there is a need to develop capabilities in data analysis and organization of information necessary for decision making. However with continued innovation revolving around digital technologies, the internet and mobile computing, the amount of data, in terms of transactions, business interaction, serial exchanges and success, continues to grow exponentially. At this rate, there will soon be a shortage of talented analysts who can help organizations work with such big data. The Business Analytics concentration within the MS degree program provides a strong foundation in ‘Data Analytics’ by bringing together a diverse body of knowledge from applied statistics, applied mathematics, computer science, optimization, consumer behavior, risk management, operations research and decision theory. The Participants will use this training to solve real problems in finance, marketing, accounting, and other disciplines.

Program Objectives:

Participants in this program will acquire knowledge in the new information systems design and development that explores how information flow is managed to enable seamless integration within organization and its value chains. On graduation the participants of this program will be prepared to assist in strategic decision-making, developing strategy necessary to drive better business results by gaining the ability to transform data into a powerful and predictive strategic asset. Business Analytics is critical in preparing organizations to solve 21st-century business challenges and participants of this program will have exposure to innovative methodologies that support data driven decision making.

Program-Structure

Duration: 2 years

Semester: 4

Courses: 8 (each course of 3 Credit hours)

Thesis: 6 Credit hours

Total Credit Hours: 30

Core Courses

  • Foundation of Data Science using Programming Language
  • Statistical Analysis for Management Research
  • Business Analytics and strategy
  • Research Methodology
  • Machine Learning

Elective Courses

  • Web Marketing and Analytics
  • Big Data Analytics
  • Deep Learning
  • Data Exploration and Visualization
  • Future, Options & Swap Strategies

MS Thesis Thesis shall be of 06 credit hours. A participant shall be allowed to start working on thesis after completing the course work of 24 credit hours with a min

Program Summary

Admission Criteria:

  • Sixteen years of education and Cumulative Grade Point Average (CGPA) of 2.5 out of 4 in any discipline
  • Passed entry test GRE General or NTS (GAT) with a minimum score of 50% OR UMT GAT (UGAT) with minimum score of 60%.

All Academic credentials must be attached with the admission form and interview Panel (PhD Committee members) will give the final decision regarding admission in MS-BA