Executive-Friendly Program | High Impact Format

Key Highlights of IIT Kanpur e-Masters Degree

  • SelectionBased on academic and professional background and test, interview where necessary. No GATE required.
  • High Impact Format Weekend-only Live interactive sessions coupled with self-paced learning.
  • Executive Friendly Schedule Learn while you earn, with the flexibility to complete the program between 1 - 3 years.
  • Career Advancement and Networking Support for placement and facilitation of incubation at IIT Kanpur's Incubation Centre.
  • IIT Kanpur Alumni Status Become an IIT Kanpur alumni with access to all the alumni privileges.
  • Credits Transfer Waiver of upto 60 credits for higher education (MTech/PhD) at IIT Kanpur.

Admission Process

  • Application
    Register with Mobile Number
    Submit Details
    Remit Application Fee
    Upload Documents
  • Selection
    Application Review
    Interview
  • Admission

Class Start - January 2025

* Selection test differs for every programme

e-Masters in Data Science and Business Analytics Course Overview

e-Masters in Data Science and Business Analytics program offers working professionals the opportunity to earn a masters degree in data science and business analytics online. This program combines the latest advancements in data science with the practical applications of business analytics, providing professionals with a comprehensive understanding of the field. The program from the Department of Management Sciences (DoMS), formerly known as Department of Industrial and Management Engineering (IME), is designed to help professionals develop the skills and knowledge needed to make data-driven decisions and solve complex business problems. The curriculum covers a wide range of topics, including data mining, machine learning, statistical modeling, big data, and more.

The Masters in Data Science and Business Analytics program is an ideal choice for individuals looking to advance their careers in this rapidly growing field. Graduates will be equipped with the skills and knowledge needed to make an impact in a variety of industries, including technology, finance, healthcare, marketing, and more. With a flexible online format, students can pursue their masters degree in data science and business analytics while balancing work and other commitments.

Graduation Ceremony at IIT Kanpur Campus

Outcomes

  • Leverage data science applications for making smart business decisions
  • Get an eMasters Degree
    from IIT Kanpur
  • Become a part of IIT Kanpur's
    alumni network
  • Learn from a leading research
    faculty group
  • Receive mentorship and career support
    from the IIT Kanpur placement cell
  • Incubation support for promising
    startup initiatives
  • Opportunity to create a meaningful network with diverse professionals

Why do participants choose the eMasters degree?

  • "I work in EDI technology, which is related to data. I believe this program will help me understand Data Science hands-on, and introduce me to tools and best practices. Also, it’s every Engineer’s dream to study at IIT. So, this program will benefit me in myriad ways; career-wise and personal goals."
    Ankit, Programming Analyst at Software Company with 2 years of experience
  • "Exposure to cognitive and prescriptive quantitative methods will provide me with the tools for decision-making beyond conventional methods. The domain electives will help me understand the quantitative methods to address the challenges business leaders face today."
    Puneet, Vice President at an International Banking Services Company with 17 years of experience

Faculty

Empower Your Career with IIT Kanpur Masters in Data Science and Business Analytics: Learn from Our Expert Faculty Group of Cutting-Edge Researchers from Various Departments, Including Economic Sciences, Department of Management Sciences (DoMS), Mathematics, and Computer Science & Engineering.

  • Vipin B
    Ph.D., Operations, IIT Madras
    Assistant Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Decision Theory, Behavioral Operations Management, Supply Chain Contracts, Optimization in Operations Management, Sustainable Operations, Healthcare Operations
  • Devlina Chatterjee
    Ph.D., Management Studies, IISc
    Associate Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Managerial Economics, Applied Econometrics, Consumer Finance, Tourism economics, Resilience of Social Systems, Empirical Finance
  • Faiz Hamid
    Ph.D., Decision Sciences & Information Systems, IIM Lucknow
    Assistant Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Operations Research, Combinatorial Optimization, Network Optimization, Data Science
  • Sri Vanamalla V
    Ph.D., Management Studies, IISc
    Associate Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Applied Operations Research, Optimization and Game Theory
  • Amey Karkare
    Ph.D., Computer Science and Engineering, IIT Bombay
    Associate Professor, Department of Computer Science and Engineering
    Research Expertise: Compilers, Data Flow Analysis, Heap Analysis
  • Arnab Bhattacharya
    Ph.D., Computer Science, Department of Computer Science - University of California, Santa Barbara
    Associate Professor, Department of Computer Science and Engineering
    Research Expertise: Databases, Data Mining, Bioinformatics
  • Subhajit Roy
    Ph.D., Computer Science and Engineering, IISc
    Associate Professor, Computer Science and Engineering
    Research Expertise: Compilers, Program Analysis, Code Optimization, Formal Methods, Artificial Intelligence, Software Engineering, Programming Languages
  • Jothsna Rajan
    Ph.D., Public Policy, IIM Bangalore
    Assistant Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Partnerships, Public Administration, Policy Evaluation
  • Veena Bansal
    Ph.D., IIT Kanpur
    Associate Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Data Science, Software Project Management, ERP
  • Abhinava Tripathi
    Ph.D., Finance and Accounting, IIM Lucknow
    Assistant Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Financial Markets, Market microstructure, Liquidity, Market Efficiency, Banking, Corporate Banking, Credit risk management in Banking, Project Finance, Investment Management, Derivatives, Security Analysis and Portfolio Management, Corporate Finance, Financial Management, Corporate Valuation and Restructuring, R programming: Quantitative applications in Finance with R, Accounting, Financial Accounting, Management Accounting
  • Suman Saurabh
    FPM (Ph.D.), IIM Ahmedabad
    Assistant Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Corporate Finance, Asset Pricing, Behavioral Finance, Mergers and Acquisitions, Financial Derivatives
  • Amit Shukla
    FPM, IIM Lucknow
    Associate Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Emerging Employment Relationship, Citizenship Behaviour, Psychological Ownership, Positive OB, Academic Excellence, Staffing, Talent and Performance Management, Marketing Communications
  • Vinay Ramani
    Ph.D., University of Buffalo
    Associate Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Economics-Operations Management Interface; Industrial Organization; Pricing Strategy
  • Avijit Khanra
    Fellow (Ph.D.), IIM Ahmedabad
    Assistant Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Inventory Control, Supply Chain Management, Production Scheduling, Analysis of queues
  • Shankar Prawesh
    Ph.D., University of South Florida, College of Business
    Associate Professor, By Department of Management Sciences (DoMS)
    Research Expertise: Social Media, Agent Based Simulation, Fairness in Big Data
  • Sourav Majumdar
    PhD (IIM Ahmedabad)
    Assistant Professor, Department of Management Sciences
    Research Expertise: Circular Statistics, Quantitative Finance, Topological Data Analysis
  • Suvendu Naskar
    Ph.D., IIM Calcutta
    Assistant Professor, Department of Management Sciences
    Research Expertise: Information Technology, Emerging Technologies, Supply Chain Management, SC Finance, Social and Organisational impact of IT
  • Jitender Kumar
    PhD (IIT Roorkee)
    Assistant Professor, Department of Management Sciences
    Research Expertise: Brand Management, Consumer Psychology, Brand Communities
  • Nivedita Bhaktha
    PhD (The Ohio State University)
    Assistant Professor, Department of Management Sciences
    Research Expertise: Psychometrics, Data Quality Assessment, Multivariate Analysis, Latent Variable Modeling, Categorical Data Analysis, Simulation Studies, Data Visualization, Survey Research, Research Methods
  • N.K. Sharma
    P.hD., University of Delhi
    Professor (Retired), Department of Management Sciences
    Research Expertise: Consumer Behaviour, Marketing, Cognition
  • Prerna Gautam
    PhD (University of Delhi)
    Assistant Professor, Department of Management Sciences
    Research Expertise: Operational Research, Optimization, Sustainability, Waste Management, Service Operations Management

e-Masters in Data Science and Business Analytics Curriculum

A well-researched real-world curriculum by IIT Kanpur’s subject matter experts that fosters hands-on learning and helps you master the desired capabilities by combining deep formal rigour and an intensely practical approach.

Modules

e-Masters in Data Science and Business Analytics consist of Core (C) and Elective (E) modules and the program has 3C + 9E structure

  • Stochastic Elements of Business
  • Linear and Non-Linear Modeling
  • Data Mining Tools & Techniques

  • Applied Machine Learning
  • Optimization Methods for Analytics
  • Temporal and Cross-Sectional Modeling
  • Causal Inference Models
  • Multivariate Data Analysis
  • Marketing Analytics
  • Financial Analytics
  • Social Media Analytics
  • Supply Chain Analytics
  • Human Resource Analytics
  • Project - 1
  • Project - 2

Detailed Curriculum

Immersive Learning Format

  • Live Interactive Sessions
  • Projects
  • Online Examination
  • Campus Visit
  • Online LIVE and self-paced sessions are delivered
    through AI-powered iPearl.ai
  • Live interaction as per the
    faculty availability
  • Apply learnings through projects while working in teams and
    establish a peer network
  • Final module-level exams will be
    conducted online
  • Opportunity to meet experts and experience the IITK campus
    during campus visits

Eligibility

  • 4 years program or Master’s degree in Engineering, Science, Economics with at least 55% marks or 5.5/10 CPI.
  • Minimum of 2 years of full time work experience (You need not be currently employed to be eligible).
  • Candidates should have had mathematics in Class 12.

Data Science and Business Analytics e-Masters: Fees

Application fee ₹1500 (to be paid during application submission)

Fee structure for candidates opting to complete the program in 1 year.

Details Amount
Registration Fee
To be paid within 1 week of selection		 ₹40,000
Admission Fee
To be paid to complete enrollment		 ₹1,60,000
Module Fee
To be paid at the beginning of every quarter based on no. of modules selected
(Total 12 Modules) 		₹5,40,000
₹45,000 per module
Quarter Fee*
To be paid at the beginning of every quarter		 ₹60,000
₹15,000 per quarter
Total Fee ₹8,00,000

*For every additional quarter, fees of Rs 15,000 will be applicable.

For Example

Candidates opting to complete the program in 5 quarters need to pay an additional fee of ₹15,000

Candidates opting to complete the program in 11 quarters need to pay an additional fee of ₹1,05,000

All other fees remain the same.

Fees paid are non-refundable (after a certain time period) and non-transferable.

About IIT Kanpur

Established in 1959 by the Government of India, Indian Institute of Technology Kanpur (IIT Kanpur) is a globally acclaimed university for world-class education and research in science, engineering, management and humanities. We aim to provide leadership in technological innovation for the growth of India.

  • Ranked 5th in Innovation, 4th in Engineering and 4th in Overall Category by NIRF 2024
  • Built on world-class academic research culture
  • Offers various undergraduate, post-graduate, integrated, and research programs in the field of engineering, science, management, and design
IIT Kanpur Online Masters Degree Courses

State-of-the-Art Digital Learning Platform

The eMasters Program by IIT Kanpur will be delivered on iPearl.ai, a State-of-the-Art digital learning platform, powered by TalentSprint. iPearl.ai, highly rated for its user experience, is a direct-to-device platform that works seamlessly on any internet-connected device and provides a single-sign on experience for all your learning needs including recorded videos, reading material, live interactive sessions, assignments, quizzes, discussion forums, virtual lounges and more.

Frequently Asked Questions

The curriculum for eMasters in Data Science and Business Analytics comprises Core (C), Advanced Electives, Domain Electives (E) modules, and Projects (P). Participants are given flexibility in deciding on electives and projects and follow the structure of 3 Core modules + 9 Electives

The Core Modules include

  • Stochastic Elements of Business:
    This is an introductory module. The emphasis will be on the practical use of data analysis techniques for visualization and summarization of data yielding useful insights. The topics covered include probability, random variables and distributions, limit theorems and point estimation, confidence intervals, hypothesis testing, and analysis of variance.
  • Linear and Non-Linear Modeling:
    This module will introduce you to regression tools that help explore causal relationships between different factors within a business environment. The topics covered include regression, linear regression with one and multiple variables, measures of fit, and heteroscedasticity.
  • Data Mining Tools & Techniques:
    The module gives an insight into data mining (DM), its theoretical foundations, tools, and techniques. Some of the topics covered include data preparation for DM, supervised and unsupervised learning, decision trees, artificial neural network, native Bayes classifier, classification evaluation, and improvement techniques.

Elective Modules

  • Applied Machine Learning:
    The module provides a sufficient theoretical understanding of various ML techniques and an opportunity to apply them to a data set using the python programming language.
  • Optimization Methods for Analytics:
    In this module, you will learn about optimization models and techniques and how to effectively apply them in solving management and engineering problems. The topics include linear programming, its applications, graphical and simplex method, duality and sensitivity analysis, numerical optimization - search, and gradient methods.
  • Temporal and Cross-Sectional Modeling:
    In this module, you will learn about some of the important forecasting tools to be applied in the context of business settings. The module further puts a spotlight on statistical analysis models like ARIMA, and exponential smoothing that uses time series data to better understand the data set or to predict future trends.
  • Causal Inference Methods:
    Here, you will be introduced to a set of econometric tools necessary for business decision-making. This is an application-based module where you will learn the importance of conducting causal analysis and how one can use it effectively to optimize business processes. The module will also deliberate on methods that are useful in drawing causal inferences like propensity score matching method, regression discontinuity method, true experiments, and quasi-experiments.
  • Multivariate Data Analysis:
    Here, you will learn to recognize the data patterns containing more than two variables as part of multivariate data analysis. In addition, you will learn how multivariate data analysis is used in the corporate environment to support decision-making. The topics covered include factor analysis, ‘R’ type factor analysis, canonical correlation analysis, conjoint analysis, cluster analysis, multidimensional scaling, and structural equation modeling.
  • Marketing Analytics:
    Through this module, you will explore how statistical tools can be used to improve marketing decisions and return on marketing investment. Topics covered include marketing analytics, pricing methods, customer lifetime value (CLV) calculation, market segmentation - cluster analysis, retailing - RFM analysis, direct mail optimization, advertising - media selection models, online business, and recommender systems.
  • Financial Analytics:
    Here, you will develop the necessary technical knowledge of building financial models and doing financial analytics using Excel NBA/R/Python. The module includes topics covering the application of data analytics in the financial markets: equity markets, fixed-income markets, and derivative markets. The module has a dedicated focus on portfolio analytics and risk management.
  • Social Media Analytics:
    Social media has changed how individuals live, buy, interact with each other and consume products, services, and information. This module aims to help you understand the complexity of network effects and how companies can use their social media data to drive their strategies and make profitable decisions.
  • Supply Chain Analytics:
    This module encompasses a detailed understanding of the design and management of a supply chain. You will also learn to critically analyze the performance of a supply chain ecosystem statistically and also get exposure to the techniques for improving the performance of a supply chain function in the organization.
  • Human Resource Analytics:
    Through this module, you will be able to impart necessary skills for quantification of human attributes and efforts and measuring their efficiency and effectiveness in producing desirable organizational outcomes. Some of the topics covered include capability planning, LAMP framework, evidence-based management (Mercer framework), and talent management audit.
  • Project - 1
  • Project - 2

View all