Executive-Friendly Program | High Impact Format |

IIT Kanpur eMasters Degree Program

eMasters in Data Science
and Business Analytics

Leverage data for strategic business decisions

  • No GATE Score
    required
  • Placement Support and
    Alumni Benefits from IIT Kanpur
  • Earn Masters Degree
    without leaving your job
  • Top Faculty from Industrial and
    Management Engineering Dept.

Apply Now

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IITK

eMasters Highlights

  • 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 Access to IIT Kanpur placement cell and 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
    Selection Test
    Interview
  • Admission

About eMasters in Data Science and Business Analytics

eMasters program in Data Science and Business Analytics aims to provide you with in-depth knowledge of cutting-edge data science tools for business analytics. The program deepens the conceptual understanding of mining and analytical techniques for descriptive and predictive analytics. The program is designed to address the needs of practitioners from diverse backgrounds in engineering, management, finance, economics, law, and public administration.

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

Faculty

Learn from IIT Kanpur’s expert faculty group drawn from the Department of Economic Sciences, Department of Industrial and Management Engineering, Department of Mathematics, and Department of Computer Science & Engineering, who are at the forefront of cutting-edge research practices.

  • Vipin B
    Ph.D., Operations, IIT Madras
    Assistant Professor, Department of Industrial and Management Engineering


    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, Department of Industrial & Management Engineering


    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, Department of Industrial and Management Engineering


    Research Expertise: Operations Research, Combinatorial Optimization, Network Optimization, Data Science
  • Sri Vanamalla V
    Ph.D., Management Studies, IISc
    Associate Professor, Department of Industrial & Management Engineering


    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
  • Wasim Ahmad
    Ph.D., Delhi University
    Associate Professor, Department of Economic Sciences


    Research Expertise: Macroeconomics, Financial Economics, Applied Econometrics, Emerging Market Finance, Risk Spillover Analysis, Clean Energy Finance

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

eMasters in Data Science and Business Analytics consist of Core (C), Specialization (S), and Electives (E) and Domain Electives (D) modules and Projects (P). Participants are given flexibility in deciding on electives and projects and follow the following structure. 3 Core Modules + 3 Modules from a basket of 5 Advanced Electives + 4 Modules from a basket of 5 Domain Electives + 2 Projects (1 project+1 elective)

  • 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

  • Business Intelligence Marketing Analytics

    Business Intelligence Financial Analytics

    Business Intelligence Social Media Analytics

    Business Intelligence Supply Chain Analytics

    Business Intelligence HR Analytics

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 across major cities in India
  • Opportunity to meet experts and experience the IITK campus during campus visits

Eligibility

  • Bachelor's degree (4 years program) in engineering, science, economics with at least 55% marks or 5.5/10 CPI
    (Or)
    Master’s degree in engineering, science, economics, commerce, management with at least 55% marks or 5.5/10 CPI
  • 2 years of work experience (an applicant need not be currently employed to be eligible).
  • Candidates should have had mathematics in Class 12.

Program Fee

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.

Fee paid are non-refundable and non-transferable

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 + 3 Modules from a basket of 5 Advanced Electives + 4/5 Modules from a basket of 5 Domain Electives + 2 Projects (1 project+1 elective)

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.
  • Fundamentals of 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.

Advanced 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.

Domain Elective Modules

  • 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.
  • HR 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.

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 4th by NIRF in the Engineering category, 2022
  • 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

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.