Program Description
The MS BA program aims to develop problem-solving skills among the students through an in-depth understanding of business analytics. This program develops unique skills in the students to analyze, synthesize and visually present data related to numerous fields of management sciences i.e., marketing, management, HR, operations and finance. The graduates of the MS BA program will be equipped with in-demand skills and knowledge required for success in their professional careers. The program is designed in a way that students with no background in business studies may also take admission in this program. However, depending on the undergraduate degree, students will be required to study deficiency courses.
Learning Outcomes
The key learning outcomes of the MS BA program are to enable our graduates:
Career Opportunities
An MS BA program can significantly expand the graduates’ career opportunities and increase their salary-earning potential. The graduates of MS BA can find a number of pathways to choose from, such as business analytics consultants, operations analysts, people analysts, financial analysts, and market or consumer analysts.
Admission Requirements
Eligibility Criteria
Selection Criteria
Degree Requirements
For the award of Master of Science in Business Analytics degree, a student must have:
Tentative Study Plan
Semester-I | Semester-II | ||||||
CS | 1001 | Programming Fundamentals* | 3+0 | BA | 5001 | Inferential Statistics & Descriptive Modelling | 3+0 |
MT | 2004 | Business Math II* | 3+0 | BA | 4001 | Introduction to Decision Science | 3+0 |
CS | 2003 | Data Structures and Business Applications* | 3+0 | MG | 3001 | Legal & Ethical Issues in Business Analytics | 3+0 |
MG | 5017 | Advanced Research Methods | 3+0 | ||||
Semester-III | Semester-IV | ||||||
BA | 3001 | Machine Learning for Business Analytics | 3+1 | BA | 5002 | Data Driven Decision Making and Optimization | 3+0 |
MG | 4014 | Econometrics | 3+0 | BA | 5003 | Predictive Modelling | 3+0 |
BA | Elective- I | 3+0 | BA | MS Project/MS Dissertation-II | 0+3 | ||
BA | Elective-II/MS Dissertation-I | 0+3 |
Note: Graduates with non-business education have to study three introductory business courses during the first two semesters. The courses marked * may be exempted for students from Computer Sciences and Engineering backgrounds
Semester-1 | |||
---|---|---|---|
Code | Course Name | Credit Hours | Course Type |
MG5017 | Advanced Research Methods | 3 | Core |
CS2003 | Data Structures and Business Applications* | 3 | Core |
MT2004 | Business Math II* | 3 | Core |
CS1001 | Programming Fundamentals* (Deficiency Course) | 3 | Core |
Semester-2 | |||
Code | Course Name | Credit Hours | Course Type |
MG3001 | Legal & Ethical Issues in Business Analytics | 3 | Core |
BA4001 | Introduction to Decision Science | 3 | Core |
BA5001 | Inferential Statistics & Descriptive Modelling | 3 | Core |
Semester-3 | |||
Code | Course Name | Credit Hours | Course Type |
BA | Elective-II/MS Dissertation-I | 3 | Core |
BA | Elective - I | 3 | Elective |
MG4014 | Econometrics | 3 | Core |
BA3001 | Machine Learning for Business Analytics | 3+1 | Core |
Semester-4 | |||
Code | Course Name | Credit Hours | Course Type |
BA | MS Project/MS Dissertation-II | 3 | Core |
BA5003 | Predictive Modelling | 3 | Core |
BA5002 | Data Driven Decision Making and Optimization | 3 | Core |