Part Time MBA in Data Science Program Syllabus & Subjects

This program covers data analytics, machine learning, data visualization, and business intelligence. You'll gain expertise in leveraging data for informed decision-making through flexible, part-time study

Part-Time MBA in Data Science Syllabus & Subjects

A Part-Time MBA in Data Science program offers a comprehensive curriculum designed to equip students with the skills and knowledge needed to excel in the field of data science and analytics. The syllabus typically covers a wide range of subjects, including foundational courses in mathematics, statistics, and programming to build a strong analytical foundation. As the program advances, students delve into more specialized areas such as machine learning, data visualization, and big data technologies. Ethics in data science, data-driven decision-making, and business intelligence are also integral components of the curriculum. Through a combination of coursework, practical projects, and case studies, students gain hands-on experience and develop the expertise required to address complex data-related challenges across various industries. This Part-Time MBA program prepares graduates for rewarding careers in data science, analytics, and business intelligence.

The table below lists some of the subject details for the Part-Time MBA with a Data Science Specialization:

Semesters	Subjects
Semester I	Managerial Economics
	Statistics for Management
	Professional Communication
	Accounting for Managers
Semester II	Legal Aspects of Business
	Business Research Methods
	Financial Management
	Data Science Foundations
Semester III	Strategic Management
	Minor Project
	Professional Ethics
	Data Mining and Machine Learning
Semester IV	Management in Action
	Social, Economic, and Ethical Issues
	Advanced-Data Science
	Major Project
Elective Subjects	Web and Social Media Analytics
	Finance and Risk Analytics
	Healthcare Analytics
	Deep Learning
	HR Analytics

Part-Time MBA in Data Science Projects

Let's look at some of the most creative Part-Time MBA in Data Science project ideas that are suitable for both experts and newcomers:

(i). Customer segmentation: For this project, data would be used to divide customers into various categories according to their demographics, interests, and purchasing patterns. Then, more successful marketing initiatives might be targeted using this data.

(ii). Fraud Detection: For this project, fraudulent transactions would be found utilizing data. This could be achieved by searching for trends in the data that point to fraud, such as atypical purchasing habits or international transactions.

(iii). Product Recommendation: For this project, clients would be given product recommendations based on data. This could be accomplished by investigating past client purchases, product evaluations, and other elements.

(iv). Demand Prediction: In this project, the demand for goods or services would be predicted using data. The inventory and staffing levels might then be optimized using this information.

(v). Data will be used in this project's risk assessment to determine the likelihood that specific occurrences will occur. Looking at historical data, financial data, and other elements could help with this.

Reference Books for Part-Time MBA in Data Science

Part-Time MBA in Data Science books provide students with a thorough general review of the subject matter and a close examination of their specific area of expertise. The following are some of the books for reference:

Name of Author	Name of Book
Rajesh Jugulum and Robert W. Eames	Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data
Dhananjoy Chatterjee	Business Analytics: Methods, Models, and Decisions
Satish Kumar R.	Business Analytics: The Science of Data-Driven Decision Making
Sandeep Kumar	Data Science: A Comprehensive Guide for Beginners
Tirthajyoti Sarkar and Shubhadeep Roychowdhury	Data Science Using Python and R
Naresh Kumar Mehta	Data Science and Analytics: Concepts, Techniques, and Applications
R. N. Prasad	Data Analytics: A Hands-On Approach
Arpan Shah	Data Science for Business: Applications, Techniques, and Tools
Goutam Chakraborty and M. R. Rao	Business Analytics: Applications to Consumer Marketing
A. K. Sharma	Data Science and Big Data Analytics: An Applied Guide for Business and Industry