MBA in Data Science Syllabus and Subjects 2024
MBA in Data Science syllabus focuses 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. The course is divided into 4 semesters.
The MBA Data Science syllabus pdf contains subjects that equip students with industry-oriented management and analytical skills to thrive in their professional careers. MBA in Data Science provides an opportunity for students to work as Data Scientists, Data Analysts, Data Engineer, etc.
Table of Contents
Semester-Wise MBA in Data Science Syllabus
MBA in Data Science course includes topics such as Machine Learning, Data Visualisation, etc. in the two-year course duration. The students undergo practical learning through projects and internships. Listed below is the semester-wise distribution of the MBA in Data Science syllabus:
First-Year MBA Data Science Syllabus
The MBA in Data Science syllabus in the first year provides insights into basic management principles and data programming for business development. Listed below are 1st year MBA Data Science subjects:
|
Semester I |
Semester II |
|
Business Communication |
Legal Aspects of Business |
|
Managerial Economics |
Human Resource Management |
|
Accounting for Managers |
Operations Management |
|
Marketing Management |
Business Research Methods |
|
Organizational Behaviour |
Applied Business Analytics |
|
Statistics for Management |
Spreadsheet Modelling II |
|
Spreadsheet Modelling I |
Introduction to Machine Learning |
|
Analytics Toolkit: Decision Science II |
Business Communication |
First-Year MBA Data Science Practical Subjects
Listed below are some practical subjects covered in the first-year MBA Data Science course:
- Spreadsheet Modelling
- Machine Learning
- Python Programming
Also, Check: Top Reasons to Pursue an MBA
Second-Year MBA Data Science Syllabus
Several subjects on SAP, Data Mining and Data Cleaning, etc are covered in the MBA in Data Science syllabus in the second year. Students will have to complete two research-based projects in the final year. Listed below are 2nd-year MBA Data Analytics subjects:
|
Semester Ⅲ |
Semester Ⅳ |
|
Econometrics |
Data Cleaning, Normalisation, and Data Mining |
|
SAP HCM |
R Programming |
|
HR Management |
SAP FICO |
|
Finance and Risk Analytics |
Stochastic Modelling |
|
Healthcare Analytics |
Project 2 |
|
Electives |
Electives |
|
Project 1 |
- |
Second-Year MBA Data Science Practical Subjects
Listed below are some practical subjects covered in the second-year MBA Data Science course:
- R Programming
- SAP
MBA in Data Science Subjects
MBA in Data Science syllabus includes core and elective subjects. Students also undergo internships and do projects in the final year. The MBA Data Science syllabus is covered through case studies and presentations prepared by the students. Listed below are the core and the elective subjects:
MBA Data Science Core Subjects
Given below are some core MBA in Data Science subjects:
- Business Economics & Market Sensing
- SAP and R Programming
- Business Communication
- Introduction to Machine Learning
- Python
- Business Finance & Accounting
- Managing Human Capital & Organisational Behaviour
- Finance and Risk Analysis
MBA Data Science Elective Subjects
Listed below are some elective MBA Data Science subjects:
- Web & Social Media Analytics
- Healthcare Analytics
- Deep Learning I
- HR Analytics
- Project Management
- Supply Chain Analytics
MBA in Data Science Subjects In Detail
The MBA in Data Science subjects are designed to equip students with the necessary skills and information about database management, business intelligence, and reporting, big data computation, etc. The topics for MBA in Data Science are underlined in the table below:
|
MBA in Data Science Subjects |
Topics |
|
Machine Learning |
Data Preprocessing Overview, Bias and Fairness in Machine Learning, SHAP Values, Reinforcement Learning Concepts, etc. |
|
Data Mining |
Data Mining Process and Lifecycle, Clustering, Data Mining Classification, Web Mining, Data Mining Tools and Software, etc. |
|
Operations Management |
Operational Strategies, Demand Forecasting, TQM Principles, Six Sigma Methodology, Facility Location and Layout Planning, etc. |
|
Data Warehousing and Database Management |
Concepts of Databases, Types of Databases, Database Design, ER Modeling, Transaction Management, Database Indexing, etc. |
|
Financial Accounting |
Financial Statements, Inventory Valuation, Ethics in Financial Accounting, Financial Analytical Tools, etc. |
College-wise MBA in Data Science Syllabus
MBA Data Science syllabus may vary from college to college based on their curriculum and program objectives. The MBA Data Science subjects taught in some top colleges are provided below:
SRM University MBA Data Science Syllabus
SRM University offers a two-year MBA in Artificial Intelligence and Data Science with specializations in Machine Learning and Business Analytics. Given below is the semester-wise MBA Artificial Intelligence and Data Science syllabus at SRM University.
|
Semester I |
Semester II |
|
Organizational Behavior and Design |
Human Resources Management |
|
Managerial Economics and Indian Economic Policy |
Corporate Finance |
|
Marketing Management |
Operations Management |
|
Financial Reporting, Statements and Analysis Statistics and Quantitative Techniques |
Legal and Business Environment Research Methods in Business |
|
Information Management |
Business Analytics |
|
Semester Ⅲ |
Semester Ⅳ |
|
Analytics Toolkit for Decision Sciences |
Advanced Machine Learning |
|
Introduction to Machine Learning |
Deep Learning – II |
|
Natural Language Processing |
Business Intelligence |
|
Artificial Intelligence and its Applications |
Big Data Management and Security |
|
Data Visualization |
Project |
|
Deep Learning – I |
- |
|
Summer Internship |
- |
Manipal University MBA in Data Science Syllabus
The MBA in Data Science subjects at Manipal University provides students with a comprehensive understanding of data science and data analytics principles. Given below are semester-wise MBA in Data Science syllabus:
|
Semester I |
Semester II |
|
Applied Statistics for Decision Making |
Business Communication |
|
Business Skills development |
Applied Business Analytics |
|
Communication Skill Development |
Financial Analysis and Reporting |
|
Business Policy and Strategic Management |
Macroeconomics in Global Economics |
|
Semester Ⅲ |
Semester Ⅳ |
|
Econometrics |
R Programming |
|
Spreadsheet Modelling |
Data Cleaning, Normalisation, and Data Mining |
|
HR Management |
SAP FICO |
|
SAP HCM |
Stochastic Modelling |
|
Project |
Project |
MBA Data Science Projects
Projects related to artificial intelligence, machine learning, etc., in the MBA Data Science syllabus, can be taken up by students. These career-oriented projects boost the confidence of students when they apply for jobs after graduation. Some of the popular projects in data science are:
- Fake News Detection Using Python
- Project On Sentiment Analysis
- Project on Influences of Climatic Patterns on the Food Chain Supply Globally
- Credit Card Fraud Detection
- Speech Emotion Recognition
- Forest Fire Prediction
- Classifying Breast Cancer
- Detection of Road Lane Lines
Also, Check: MBA Project Topics
MBA in Data Science Course Structure
MBA in Data Science syllabus focuses on building holistic knowledge of data science. The course structure comprises a mix of theoretical knowledge along with practical training through projects, research papers, group discussions, and internships. The MBA Data Science course structure includes:
- IV Semesters
- Core and Elective Subjects
- Projects
- Research Papers
- Surveys
- Seminars
- Practicals
- Thesis Writing
MBA in Data Science Teaching Methodology and Techniques
The teaching methodology adopted to teach concepts in the Data Science MBA syllabus involves a mix of classroom training along with solving real-world applications through case studies. This helps students in building a comprehensive understanding of data science and analysis. Some teaching techniques used by colleges are:
- Group Discussions
- Field Trips
- Problem-based Learning
- Projects
- E-learning
- Co-curricular Activities
MBA in Data Science Reference Books
The books for MBA Data Science help students understand the concepts of Data Analysis through Python, Predictive Analytics, Big Data, etc. Listed below are some popular reference books for MBA in Data Science syllabus:
|
Books |
Topics Covered |
Author |
|
Introduction to Machine Learning with Python: A Guide for Data Scientists |
Types of Machine Learning, Neural Networks, Python Basics, etc. |
Andreas C. Müller |
|
R for Data Science |
Data Visualization, Data Transformation, Model Building, etc. |
Hadley Wickham |
|
Big Data MBA: Driving Business Strategies with Data Science |
Business Value of Data, Data Science Process and Methodology, Data Governance, etc. |
Bill Schmarzo |
|
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking |
Predictive Modelling, Model Evaluation and Deployment, A/B Testing, etc. |
Tom Fawcett |
|
Data Science for Executives |
Data Science Tools and Technologies, Risk Management and Fraud Detection, Data Communication,etc. |
Nir Kaldero |
Top MBA in Data Science Colleges
Top Management Entrance Exams
Exam Date: May 19, 2024
MBA in Data Science Fee Structure
FAQs
What are some important subjects taught in MBA Data Science?
Finance and Risk Analytics, Introduction to Machine Learning, Python, etc., are some core subjects in MBA Data Science.
What are the elective subjects covered in MBA in Data Science syllabus?
Healthcare Analytics, HR Analytics, Supply Chain Analytics, etc., are some elective subjects taught in the course.
What are the subjects taught in the first year of MBA Data Science?
Applied Business Analytics, Spreadsheet Business Modelling, Business Communication, etc are some subjects taught in the first year of MBA Data Science.
Is MBA good in Data Science?
Yes, an MBA degree in Data Science offers a variety of concepts on programming and data management and gives students plenty of job opportunities.
What are some best projects in MBA Data Science?
Projects on Fake News Detection Using Python, Forest Fire Prediction, Sentimental Analysis, etc., are some of the most demanding projects in data science.
Which is better: an MBA in Data Science or Data Analytics?
Both are equally good. MBA in Data Science focuses more on managerial concepts while MBA in Data Analytics includes technical aspects related to programming and machine learning.