Sharda School of Business Studies (SBS)
SBS0135
Post Graduate
2 Years
The MBA in Business Analytics and Artificial Intelligence (AI) programme at Sharda University prepares students to analyse business data, identify trends and make informed decisions using modern analytical tools and AI technologies. The programme combines business management principles with practical knowledge of data analytics, machine learning and artificial intelligence.
Students gain an understanding of responsible AI, digital governance, big data analytics, data visualisation and storytelling, and data mining using R and Python. The curriculum also covers predictive and prescriptive analytics, time series analysis, generative AI, prompt design, machine learning and SQL for data management.
The programme further explores cloud computing, deep learning, blockchain applications, decision support systems, causal inference, A/B testing and Natural Language Processing (NLP). These areas help students understand how organisations use data and AI-driven insights to solve business problems, improve processes and support strategic decision-making.
Graduates of the MBA in Business Analytics and AI programme can pursue career opportunities as Business Analysts, Data Analysts, Analytics Consultants, AI Product Managers, AI Project Managers and Decision Science Specialists across industries.
Program Educational Objectives (PEOs)
Program Outcomes (PO’s)
Program Specific Outcomes (PSOs)
Have a strong logical and analytical aptitude with a background of Mathematics Statistics or Operations Research are an ideal fit for this program.
A future career in the field of integrated statistical analysis data mining predictive modelling business intelligence and optimisation methodologies having great decision-making ability are a perfect fit for this program.
| 1st Year 425000 | 2nd Year 437750 |
| Fee Per Semester | Fee Per Year |
|---|---|
| NA | 6000** |
|
S. .No. |
Courses |
Teaching Load |
Credits |
Core/Elective Pre- Requisite/ Co Requisite |
||
|
L |
T |
P* |
||||
|
|
Organizational Behaviour (With Personal Growth Lab) |
2 |
0 |
2 |
3 |
Core |
|
|
Economics for Managers |
1 |
0 |
2 |
2 |
Core |
|
|
Accounting & Financial Literacy for Managers |
3 |
0 |
0 |
3 |
Core |
|
|
Quantitative Methods & Data Literacy |
2 |
0 |
2 |
3 |
Core |
|
|
Legal Aspects of Business |
2 |
0 |
0 |
2 |
Core |
|
|
AI Strategy & Digital Business |
1 |
0 |
2 |
2 |
Core |
|
|
Entrepreneurial Mindset |
2 |
0 |
0 |
2 |
Core |
|
|
Marketing Management I |
3 |
0 |
0 |
3 |
Core |
|
|
Management Science |
1 |
0 |
2 |
2 |
Core |
|
|
Data Tools for Managers (Lab) |
0 |
0 |
4 |
2 |
Core |
|
|
Business Communication & Storytelling (Lab) |
1 |
0 |
4 |
3 |
Core |
|
|
Community Connect (Audit) |
0 |
0 |
4 |
0 |
Audit |
|
TOTAL CREDITS |
27 |
|
||||
|
S. No. |
Courses |
Teaching Load |
Credits |
Core/Elective Pre- Requisite/ Co Requisite |
||
|
L |
T |
P |
||||
|
THEORY COURSES |
||||||
|
|
Macroeconomics and Business Environment |
3 |
0 |
0 |
3 |
Core |
|
|
Corporate Finance |
3 |
0 |
0 |
3 |
Core |
|
|
Project Management |
2 |
0 |
0 |
2 |
Core |
|
|
Business Research Methods |
2 |
0 |
2 |
3 |
Core |
|
|
Human Resource Management |
2 |
0 |
0 |
2 |
Core |
|
|
Ethics, ESG & AI Governance |
1 |
0 |
2 |
2 |
Core |
|
|
Operations & Supply Chain Management |
3 |
0 |
0 |
3 |
Core |
|
|
Management Accounting & Decision Control |
1 |
0 |
2 |
2 |
Core |
|
|
Marketing Management II |
2 |
0 |
0 |
2 |
Core |
|
|
Business Analytics & GenAI Practical (Lab) |
1 |
0 |
4 |
3 |
SEC |
|
|
Business Simulation |
1 |
0 |
2 |
2 |
SEC |
|
|
Design Thinking (Audit) |
0 |
0 |
2 |
0 |
Audit |
|
TOTAL CREDITS |
27 |
|
||||
|
S. No. |
Courses |
Teaching Load |
Credits |
Core/Elective |
||
|
L |
T |
P |
||||
|
1 |
Strategic Management |
3 |
0 |
0 |
3 |
Core |
|
2 |
Career Lab |
0 |
0 |
2 |
1 |
Core |
|
3 |
Responsible AI and Digital Governance |
3 |
0 |
0 |
3 |
DSC |
|
4 |
Big Data Analytics |
2 |
0 |
2 |
3 |
DSC |
|
5 |
Data Visualization and Storytelling |
0 |
0 |
6 |
3 |
DSC |
|
6 |
Data Mining Using R and Python |
0 |
0 |
6 |
3 |
DSC |
|
7 |
Predictive and Prescriptive Analytics using Python |
1 |
0 |
4 |
3 |
DSC |
|
8 |
Time Series Analysis |
1 |
0 |
4 |
3 |
DSC |
|
9 |
Generative AI and Prompt Design |
1 |
0 |
4 |
3 |
DSC |
|
10 |
Machine Learning and Applications |
1 |
0 |
4 |
3 |
DSC |
|
11 |
SQL and Data Management |
1 |
0 |
4 |
3 |
DSC |
|
12 |
MOOC |
0 |
0 |
2 |
1 |
Core |
|
13 |
Summer Internship Project and Presentation |
0 |
0 |
6 |
3 |
Core |
|
Total Credits |
35 |
|
||||
|
S. No. |
Courses |
Teaching Load |
Credits |
Core/Elective |
|
||||
|
L |
T |
P |
|
|
|||||
|
Theory Courses |
|
||||||||
|
1 |
Cloud Computing |
2 |
0 |
2 |
3 |
DSC |
|||
|
2 |
Artificial Intelligence and Deep Learning |
2 |
0 |
2 |
3 |
DSC |
|||
|
3 |
Blockchain Applications for Managers |
2 |
0 |
2 |
3 |
DSC |
|||
|
4 |
Decision Support System |
3 |
0 |
0 |
3 |
DSC |
|||
|
5 |
Causal Inference and Experimental A/B Testing |
1 |
0 |
4 |
3 |
DSC |
|||
|
6 |
Natural Language Processing and Text Analytics |
1 |
0 |
4 |
3 |
DSC |
|||
|
7 |
Dissertation/Capstone Project |
0 |
0 |
6 |
3 |
Core |
|||
|
TOTAL CREDITS |
21 |
|
|
||||||
| S.No. | Academic year | Curricula Link |
|
1 |
2025-26 | View Details |
|
2 |
2024-25 | View Details |
|
3 |
2023-24 | View Details |
|
4 |
2021-22 | View Details |
|
5 |
2020-21 | View Details |
|
6 |
2019-20 | View Details |
|
7 |
2018-19 | View Details |
| For National Students | MBA Business Analytics eligibility criteria include:
OR
OR
|
| For International Students | The eligibility criterion for all programs for international applicants is minimum 50% in the qualifying examination and having studied the pre-requisite subjects for admission in to the desired program. |
Students of this programme are placed in companies with an average annual package of 3.52 LPA to 9.60 LPA