IPE Launched its two-year AICTE approved full time PGDM- Business Analytics Program for the academic year 2024-25 to meet the growing requirements of Analytics professionals. This Programme is mainly oriented towards imparting skills in analytics arena desired by the global and domestic business entities. The curriculum intends to reduce the gap between industry and academia, with the right blend of theory and practice, furthering students to nurture their innate talent for becoming business analysts, business intelligence analyst, marketing analyst, financial analyst, quantitative analyst, Risk analyst thus becoming invaluable and indispensable assets of an organization. Being a student of this program you would be able to gain an in- depth knowledge and analytical skills which will enable them to carry out various Trade and Business operations of an organization effectively and efficiently in the emerging globalized environment. This program has an intake of 60 students.
For admission procedure, fee details and scholarships refer to IPE admission prospectus.
|
Trimester I |
|
| Course Name | Credits |
| Management and Organizational Behaviour | 3 |
| Business Statistics for Decision Making | 3 |
| Economics for Managers | 3 |
| Accounting for Managers | 3 |
| Marketing Management | 3 |
| Information Technology for Managers | 3 |
| Personality Development and Business Communication | Letter Grade |
| Total Credits | 18 |
|
Trimester II |
|
| Course Name | Credits |
| Operations Research | 3 |
| Corporate Finance | 3 |
| Macro Economics | 3 |
| Human Resource Management | 3 |
| SQL for Managers | 2 |
| Business Analytics for Managers using R | 3 |
| Big Data for Business Decisions | 2 |
| Priming for Placements (Business Aptitude) | Letter Grade |
| Total Credits | 19 |
|
Trimester III |
|
| Course Name | Credits |
| Production and Operations Management | 3 |
| Cost and Management Accounting | 2 |
| Start-ups and Entrepreneurship | 3 |
| Marketing Research | 3 |
| Machine Learning using Python | 3 |
| Data Analytics using SAS | 2 |
| Data Visualization and Story Telling | 3 |
| Foreign Language – French | Letter Grade |
| Comprehensive Viva | 1 |
| Total Credits | 20 |
|
Trimester IV |
|
| Course Name | Credits |
| Strategic Management | 3 |
| Business Applications using Deep Learning and Artificial Intelligence | 3 |
| Social Media & Web Analytics | 2 |
| Elective 1(Analytics) – Subject 1 | 3 |
| Elective 1(Analytics) – Subject 2 | 3 |
| Elective 2 – Subject 1 | 3 |
| Elective 2 – Subject 2 | 3 |
| Summer Internship Project | 3 |
| Total Credits | 23 |
|
Trimester V |
|
| Course Name | Credits |
| Corporate Laws | 2 |
| Natural Language Processing | 3 |
| Generative AI | 3 |
| Elective 1(Analytics) – Subject 3 | 3 |
| Elective 1(Analytics) – Subject 4 | 3 |
| Elective 2 – Subject 3 | 3 |
| Elective 2 – Subject 4 | 3 |
| Total Credits | 20 |
|
Trimester VI |
|
| Course Name | Credits |
| Corporate Governance, Business Ethics, and CSR | 2 |
| Project Management | 2 |
| Long Term Research Project | 2 |
| Total Credits | 6 |
| S.No | Elective Subject Name (Subject 1, Subject 2) | Credits |
|---|---|---|
| 1 | Marketing Analytics | 3 |
| 2 | Operations Analytics | 3 |
| 3 | Financial Analytics | 3 |
| 4 | HR Analytics | 3 |
| S.No | Elective Subject Name (Subject 1, Subject 2) | Credits |
|---|---|---|
| 5 | Data Science and Machine Learning | 3 |
| 6 | Business Intelligence and Data Visualization | 3 |
| 7 | SQL for Data Science | 3 |
| S.No | Elective Subject Name (Subject 1, Subject 2) | Credits |
|---|---|---|
| 8 | Cyber Security and Cyber Laws | 3 |
| 9 | Predictive Analytics | 3 |
| 10 | Data Mining for Business Decisions | 3 |
Note: Business Analytics Programme students need to take Subject 1 from SET 1 and Subject 2 from SET 3 whereas other Programme students choosing Analytics as specialization choose Subject 1 and Subject 2 from SET 2 and SET 3.
| S.No | Elective Subject Name (Subject 3, Subject 4) | Credits |
|---|---|---|
| 1 | Big Data Analytics | 3 |
| 2 | IOT Data Management and Analytics | 3 |
| 3 | Cloud Computing for Business | 3 |
| 4 | Artificial Intelligence and Deep Learning | 3 |
| 5 | Blockchain Technology for Business | 3 |
Note: Business Analytics Programme students as well as other Programme students choosing Analytics as specialization choose Subject 3 and Subject 4 from SET 4.
