MBA in Data Science syllabus and subjects is unique as it blends business management with analytical skills. These programs focus on giving a holistic understanding of data science and building cross-functional management skills among students. Important MBA Data Science subjects are business analytics, artificial intelligence, machine learning, etc. MBA in Data Science includes both core and elective subjects. In the first year of an MBA in Data Science, students learn the core subjects, while in the second year, they move towards specialized and elective subjects.
The course is divided into four semesters over two years. Students study core subjects in the first year and then move to elective subjects according to their interest in the second year. The course also focuses on practical learning through projects and internships. Listed below is the semester wise distribution of the syllabus:
| Semester I | Semester II |
|---|---|
| Business Communication | Corporate Finance |
| Managerial Economics | Human Resource Management |
| Principles of Management | Operations Management |
| Marketing Management | Statistical Modelling |
| Organizational Behaviour | Data Visualisation |
| Statistics for Business: Decision Science I | Spreadsheet Modelling II |
| Spreadsheet Modelling I | Introduction to Machine Learning |
| Analytics toolkit: Decision Science II | Entrepreneurial Development |
| Semester Ⅲ | Semester Ⅳ |
|---|---|
| Advanced Machine Learning | Applications of Deep Learning |
| Natural Language Processing | Applications of Natural Language |
| Web & Social Media Analytics | Supply Chain Analytics |
| Finance and Risk Analytics | HR Analytics |
| Healthcare Analytics | Marketing Analytics |
| Deep Learning I | Project Management |
MBA in Data Science includes two types of subjects-one Core and the other elective subjects. Along with this internship and project submission is there. Also, the learning in MBA Data Science is done through group discussions and presentations prepared by the students. Listed below are the core and the elective subjects:
Core Subjects:
Elective Subjects:
MBA Data Science syllabus focuses on building holistic learning of data science. In the first year, subjects are generic subjects studied in all MBA courses. While in the second year subjects become specialized to the particular field and also some subjects become elective. In this way, students can choose the subjects which are of interest to them. The course structure is a mix of theoretical knowledge along with practical use of this knowledge through projects, research papers, group discussions, and also internships. The course structure includes:
The teaching methodology can be very different for MBA Data Science. It involves a mix of classroom teaching along with the real-world application of this knowledge through case study learning. This teaching methodology help in building a comprehensive understanding of Data Science. Through this methodology, students can understand the world of artificial intelligence, machine learning, etc. Some methodology techniques used by colleges are:
Projects in data science can be about various topics related to artificial intelligence, machine learning, etc. These projects help in boosting the confidence of students by applying the practical use of their learnings and help them in making better leaders and decision-makers. These projects can be of many types as the application of data science is in many fields. Some popular projects are:
Listed below are some popular reference books used in MBA Data Science courses:
| Books | Author |
| The Signal and the Noise | Nate Silver |
| Business Research Methods Donald | R. Cooper |
| Introduction to Machine Learning with Python: A Guide for Data Scientists | Andreas C. Müller |
| R for Data Science | Hadley Wickham |
| Big Data MBA: Driving Business Strategies with Data Science | Bill Schmarzo |
| Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking | Tom Fawcett |
