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DETAILS
This MBA Digital Business with specialization in Data Mining course deals with the inter-combination of statistics and computer science with an aim to extract patterns of information from given raw data (unprocessed data) and transform the data to provide meaningful information for business use. It covers the concepts of machine learning used as data mining techniques and touches upon the differences between data science and data mining. Students will be able to use the different data mining techniques such as association, clustering, and use different data mining applications such as market basket analysis and customer relationship management. KPMG will be a part of the curriculum design and implementation process; prospective employers will also find this program appropriate because it will help them cut short the time required to train MBAs before they can become productive in the workplace.
MBA Business Analytics in collaboration with KPMG
- Co-delivered by KPMG experts
- Includes an industry-relevant capstone project
- One-on-one interaction with industry mentors
- Networking opportunities
- Experiential learning: Hands-on experience in leading industry tools and technology
Duration of Program
2 years (4 Semesters)
Seats
20*
Co-Delivered Courses by Partner Industries
DESIGN YOUR OWN DEGREE
UPES’ curriculum framework is holistic in its overall structure and yet focuses on the individual need of the student to discover, experience, explore and challenge. Along with the core subject, students have the option to choose from subject-focused specialisations. They are also allowed to choose minor/exploratory subject from other schools at UPES that are: School of Engineering, School of Computer Science, School of Law, School of Business, School of Health Sciences, School of Design, School of Modern Media, and School of Liberal Studies.
Further, based on the multifaceted needs of the global workplace and evolving lifestyles, the curriculum offers Signature and Life-Skills courses through School for Life. To round off this learning experience, students are required to do mandatory internships in the social sector, government/public sector, and industry. The combinations available for students to pick and choose from are endless, ensuring both depth and width of knowledge.
- Data Scientist in multi-national corporations
- Quantitative Analyst roles in investment banking units
- Consultant or Senior consultant roles
- Big Data Analyst
- Data Warehousing Expert
- Business Intelligence Expert
- Data Mining Expert
- Candidates can pursue higher studies
Minimum 50% marks in Class X & XII and Graduation. Graduation From a recognized University in any stream.
UPESMET / National Level Exams/ CUET followed by Personal Interview
Course Credits
| Course | Credits | Percentage |
|---|---|---|
| Major Foundation | 30 | 29% |
| Major Core | 32 | 30% |
| Specialization | 6 | 6% |
| Dissertation | 6 | 6% |
| Life Skills | 10 | 10% |
| Signature | 9 | 9% |
| Minor/Exploratory | 9 | 9% |
| Internships and Industry Visit | 3 | 3% |
| Total | 105 | 100% |
| SFLI Total | 28 | 27% |
SEMESTER I
| Subject Code | Subject | Credits |
|---|---|---|
| HRES 7002 | Management Principles and Organisational Behaviour | 3 |
| FINC 7010 | Accounting for Managers | 3 |
| ECON 7006 | Managerial Economics | 3 |
| MKTG 7001 | Marketing Management | 3 |
| DSQT 7001 | Quantitative Methods | 3 |
| HRES 7004 | Business Communication | 3 |
| DSBA 7002 | Data Environment | 3 |
| DSBA 7001 | Business Modelling with Spreadsheets | 3 |
| SLICL01 | Learning How to learn | 2 |
| SLICL02 | Living Conversations | 2 |
| TOTAL | 28 |
SEMESTER II
| Subject Code | Subject | Credits |
|---|---|---|
| HRES 7007 | Human Resource Management | 3 |
| FINC 7019 | Financial Management | 3 |
| DSRM 7002 | Business Research Methods | 3 |
| DSQT 7002 | Operations Research | 3 |
| DSBA 7004 | Data Management | 3 |
| DSBA 7005 | Business Analytics | 3 |
| DSBA 7006 | Business Intelligence | 3 |
| Specialization Paper I | 3 | |
| SLICS01 | Critical Thinking and Writing | 3 |
| INDT 7101 | Industrial Visit | 1 |
| SLICL03 | Leadership and Teamwork | 2 |
| Minor/Exploratory I | 3 | |
| TOTAL | 33 |
SEMESTER III
| Subject Code | Subject | Credits |
|---|---|---|
| STGM 8001 | Strategic Management | 3 |
| DSBA 8006 | Supply Chain Analytics | 3 |
| DSBA 8002 | Big Data Analytics | 3 |
| Specialization Paper II | 3 | |
| SIIB 8101 | Summer Internship | 2 |
| DIST 8101 | Dissertation-I | 2 |
| SLICL04 | Design Thinking | 2 |
| SLICS02 | Ethical Leadership in the 21st Century (Human Values and Ethics) | 3 |
| Minor/Exploratory II | 3 | |
| TOTAL | 24 | |
| Specialization 1 | ||
| Energy Analytics | ||
| DSBA 8007 | Overview of Energy Analytics | |
| DSBA 8001 | Data Visualization |
SEMESTER IV
| Subject Code | Subject | Credits |
|---|---|---|
| DSBA 8009 | Social & Web Analytics | 2 |
| DSBA 8003 | Predictive Modeling | 3 |
| DSBA 8004 | Programming for Analytics | 3 |
| DIST 8102 | Dissertation-II | 4 |
| SLICS03 | Environment and Sustainability - Himalaya Fellowship | 3 |
| SLICL05 | Working with Data | 2 |
| Minor/Exploratory III | 3 | |
| TOTAL | 20 | |
| Specialization 2 | ||
| Data Mining | ||
| DSBA 7008 | Overview of Data Mining | |
| HRES 2011 | Business Process Management |
Life Skills
| Life Skills | Credits | |
| Learning how to learn | 2 | Life Skill I |
| Living Conversations | 2 | Life Skill II |
| Leadership and Teamwork | 2 | Life Skill III |
| Design Thinking | 2 | Life Skill IV |
| Working With Data | 2 | Life Skill V |
Signature
| Signature | Credits | |
| Critical Thinking and Writing | 3 | Signature 1 |
| Ethical Leadership in the 21st Century (Human Values and Ethics) | 3 | Signature II |
| Environment and Sustainability - Himalaya Fellowship | 3 | Signature III |
Career Prospects
- Data Scientist in multi-national corporations
- Quantitative Analyst roles in investment banking units
- Consultant or Senior consultant roles
- Big Data Analyst
- Data Warehousing Expert
- Business Intelligence Expert
- Data Mining Expert
- Candidates can pursue higher studies
Eligibility
Minimum 50% marks in Class X & XII and Graduation. Graduation From a recognized University in any stream.
Selection Criteria
UPESMET / National Level Exams/ CUET followed by Personal Interview
Curriculum
Course Credits
| Course | Credits | Percentage |
|---|---|---|
| Major Foundation | 30 | 29% |
| Major Core | 32 | 30% |
| Specialization | 6 | 6% |
| Dissertation | 6 | 6% |
| Life Skills | 10 | 10% |
| Signature | 9 | 9% |
| Minor/Exploratory | 9 | 9% |
| Internships and Industry Visit | 3 | 3% |
| Total | 105 | 100% |
| SFLI Total | 28 | 27% |
SEMESTER I
| Subject Code | Subject | Credits |
|---|---|---|
| HRES 7002 | Management Principles and Organisational Behaviour | 3 |
| FINC 7010 | Accounting for Managers | 3 |
| ECON 7006 | Managerial Economics | 3 |
| MKTG 7001 | Marketing Management | 3 |
| DSQT 7001 | Quantitative Methods | 3 |
| HRES 7004 | Business Communication | 3 |
| DSBA 7002 | Data Environment | 3 |
| DSBA 7001 | Business Modelling with Spreadsheets | 3 |
| SLICL01 | Learning How to learn | 2 |
| SLICL02 | Living Conversations | 2 |
| TOTAL | 28 |
SEMESTER II
| Subject Code | Subject | Credits |
|---|---|---|
| HRES 7007 | Human Resource Management | 3 |
| FINC 7019 | Financial Management | 3 |
| DSRM 7002 | Business Research Methods | 3 |
| DSQT 7002 | Operations Research | 3 |
| DSBA 7004 | Data Management | 3 |
| DSBA 7005 | Business Analytics | 3 |
| DSBA 7006 | Business Intelligence | 3 |
| Specialization Paper I | 3 | |
| SLICS01 | Critical Thinking and Writing | 3 |
| INDT 7101 | Industrial Visit | 1 |
| SLICL03 | Leadership and Teamwork | 2 |
| Minor/Exploratory I | 3 | |
| TOTAL | 33 |
SEMESTER III
| Subject Code | Subject | Credits |
|---|---|---|
| STGM 8001 | Strategic Management | 3 |
| DSBA 8006 | Supply Chain Analytics | 3 |
| DSBA 8002 | Big Data Analytics | 3 |
| Specialization Paper II | 3 | |
| SIIB 8101 | Summer Internship | 2 |
| DIST 8101 | Dissertation-I | 2 |
| SLICL04 | Design Thinking | 2 |
| SLICS02 | Ethical Leadership in the 21st Century (Human Values and Ethics) | 3 |
| Minor/Exploratory II | 3 | |
| TOTAL | 24 | |
| Specialization 1 | ||
| Energy Analytics | ||
| DSBA 8007 | Overview of Energy Analytics | |
| DSBA 8001 | Data Visualization |
SEMESTER IV
| Subject Code | Subject | Credits |
|---|---|---|
| DSBA 8009 | Social & Web Analytics | 2 |
| DSBA 8003 | Predictive Modeling | 3 |
| DSBA 8004 | Programming for Analytics | 3 |
| DIST 8102 | Dissertation-II | 4 |
| SLICS03 | Environment and Sustainability - Himalaya Fellowship | 3 |
| SLICL05 | Working with Data | 2 |
| Minor/Exploratory III | 3 | |
| TOTAL | 20 | |
| Specialization 2 | ||
| Data Mining | ||
| DSBA 7008 | Overview of Data Mining | |
| HRES 2011 | Business Process Management |
Life Skills
| Life Skills | Credits | |
| Learning how to learn | 2 | Life Skill I |
| Living Conversations | 2 | Life Skill II |
| Leadership and Teamwork | 2 | Life Skill III |
| Design Thinking | 2 | Life Skill IV |
| Working With Data | 2 | Life Skill V |
Signature
| Signature | Credits | |
| Critical Thinking and Writing | 3 | Signature 1 |
| Ethical Leadership in the 21st Century (Human Values and Ethics) | 3 | Signature II |
| Environment and Sustainability - Himalaya Fellowship | 3 | Signature III |
Non Examination Pathway
MBA Admissions through National Level Tests**
Students having minimum eligible MAT /CMAT 2023 score of 70 Percentile will be exempted from UPES Management Entrance Test and will only be called for Group Discussion and Interview if qualified. Valid 50 percentile and above score of CAT 2022/ XAT 2023 A score of minimum 400 or above for GMAT, a score of 120 and above in NMAT 2022 / 23 scores will also be accepted.
**Upto 30% seats shall be filled through National Level Tests category (CAT/MAT/XAT/NMAT). Incase candidates for such seats are not available, UPES has the right to fill these seats through MBA (UPESMET)
