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 (For Business graduate)
Sr. No | Course Name | Crdt Hrs. |
Semester 1 | ||
CS2010 | Programming Fundamentals* | 3+0 |
BA5005 | Applied Calculus for Business* | 3+0 |
CS5059 | Database System* | 3+0 |
MG5011 | Advanced Research Methods | 3+0 |
Sr. No | Course Name | Crdt Hrs. |
Semester 2 | ||
BA5001 | Inferential Statistics & Descriptive Modelling | 3+0 |
MG5047 | Decision Science for Business | 3+0 |
MG5048 | Ethical & legal Issues in Business Analytics | 3+0 |
Sr. No | Course Name | Crdt Hrs. |
Semester 3 | ||
BA5004 | Machine Learning for Business Analytics | 3+1 |
MG5050 | Econometrics | 3+0 |
XXXX | Elective- I | 3+0 |
XXXX | Elective-II/MS Dissertation-I | 0+3 |
Sr. No | Course Name | Crdt Hrs. |
Semester 4 | ||
BA5002 | Data Driven Decision Making and Optimization | 3+0 |
BA5003 | Predictive Modelling | 3+0 |
BA5090 | MS Project/MS Dissertation-II | 0+3 |
Tentative Study Plan (For Non-Business graduate)
Sr. No | Course Name | Crdt Hrs. |
Semester 1 | ||
AF4010 | Accounting and Finance for Managers* | 3+0 |
MG4005 | Business Economics for Managers* | 3+0 |
MG5006 | Marketing Analytics* | 3+0 |
MG5011 | Advanced Research Methods | 3+0 |
Sr. No | Course Name | Crdt Hrs. |
Semester 2 | ||
BA5001 | Inferential Statistics & Descriptive Modelling | 3+0 |
MG5047 | Decision Science for Business | 3+0 |
MG5048 | Ethical & legal Issues in Business Analytics | 3+0 |
Sr. No | Course Name | Crdt Hrs. |
Semester 3 | ||
BA5004 | Machine Learning for Business Analytics | 3+1 |
MG5050 | Econometrics | 3+0 |
XXXX | Elective- I | 3+0 |
XXXX | Elective-II/MS Dissertation-I | 0+3 |
Sr. No | Course Name | Crdt Hrs. |
Semester 4 | ||
BA5002 | Data Driven Decision Making and Optimization | 3+0 |
BA5003 | Predictive Modelling | 3+0 |
BA5090 | MS Project/MS Dissertation-II | 0+3 |
Note 1: Registration in "MS Thesis-I" is allowed provided the student has:
21 credits
Passed the “Advanced Research Methods” course.
CGPA is equal to or more than 2.5
Semester-1 | |||
---|---|---|---|
Code | Course Name | Credit Hours | Course Type |
MG5017 | Advanced Research Methods | 3 | Core |
CS2010 | Programming Fundamentals* (Business Graduate Student) | 3 | Core |
BA5005 | Applied Calculus for Business* (Business Graduate student) | 3 | Core |
CS5059 | Database System * (Business Graduate student) | 3 | Core |
AF4010 | Accounting and Finance for Managers ** (Non-Business Graduate student) | 3 | Core |
MG4005 | Business Economics for Managers ** (Non-Business Graduate student) | 3 | Core |
MG5006 | Marketing Analytics ** (Non-Business Graduate student) | 3 | Core |
Semester-2 | |||
Code | Course Name | Credit Hours | Course Type |
BA5001 | Inferential Statistics & Descriptive Modelling | 3 | Core |
MG5047 | Decision Science for Business | 3 | Core |
MG3001 | Ethical & Legal Issues in Business Analytics | 3 | Core |
Semester-3 | |||
Code | Course Name | Credit Hours | Course Type |
BA3001 | Machine Learning for Business Analytics | 3+1 | Core |
MG4014 | Econometrics | 3 | Core |
BA | Elective - I | 3 | Elective |
BA | Elective-II/MS Dissertation-I | 3 | Core |
Semester-4 | |||
Code | Course Name | Credit Hours | Course Type |
BA5002 | Data Driven Decision Making and Optimization | 3 | Core |
BA5003 | Predictive Modelling | 3 | Core |
BA | MS Project/MS Dissertation-II | 3 | Core |