Naveen Jindal School of Management
Master of Science in Business Analytics
36 semester credit hours minimum
Faculty
Professors: Ashiq Ali, Alain Bensoussan, Gary Bolton, Metín Çakanyildirim, Huseyin Cavusoglu, Jianqing Chen, William M. Cready, Milind Dawande, Gregory G. Dess, Umit G. Gurun, Dorothée Honhon, Kyle Hyndman, Varghese S. Jacob, Sanjay Jain, Ganesh Janakiraman, Elena Katok, Dmitri Kuksov, Nanda Kumar, Seung-Hyun Lee, Stanley Liebowitz, Zhiang (John) Lin, Sumit K. Majumdar, Stanimir Markov, Amit Mehra, Syam Menon, Vijay S. Mookerjee, B. P. S. Murthi, Vikram Nanda, Özalp Özer, Mike W. Peng, Hasan Pirkul, Cuili Qian, Suresh Radhakrishnan, Srinivasan Raghunathan, Ram C. Rao, Brian Ratchford, Michael J. Rebello, Gil Sadka, Sumit Sarkar, Suresh P. Sethi, Kathryn E. Stecke, Riki Takeuchi, Wing Kwong (Eric) Tsang, Jun Xia, Ying Xie, Harold Zhang, Zhiqiang (Eric) Zheng
Associate Professors: Mehmet Ayvaci, Nina Baranchuk, Zhonglan Dai, Rebecca Files, Michael Hasler, Bin Hu, Surya N. Janakiraman, Robert L. Kieschnick Jr., Atanu Lahiri, Jun Li, Ningzhong Li, Maria Loumioti, Lívia Markóczy, Ramachandran (Ram) Natarajan, Naim Bugra Ozel, H. Dennis Park, Anyan Qi, Young U. Ryu, Serdar Simsek, Harpreet Singh, Upender Subramanian, Shaojie Tang, Shouqiang Wang, Kelsey D. Wei, Han (Victor) Xia, Yexiao Xu, Alejandro Zentner, Jieying Zhang, Yuan Zhang, Zhe (James) Zhang, Feng Zhao, Yibin Zhou
Assistant Professors: Khai Chiong, Rafael Copat, Soraya Fatehi, Andrew Frazelle, Ying Huang, Joonhwi Joo, Sora Jun, Jason Kautz, Tongil Kim, Sheen Levine, Christopher Mace, Samir Mamadehussene, Jean-Marie Meier, Radha Mookerjee, Jedson Pinto, Ignacio Rios Uribe, Alejandro Rivera Mesias, Simon Siegenthaler, Kirti Sinha, Xiaoxiao Tang, Shervin Tehrani, Ashwin Venkataraman, Christian Von-Drathen, Guihua Wang, Hongchang Wang, Pingle Wang, Junfeng Wu, Steven Xiao, Yingjie Zhang
Professor Emeritus: John J. Wiorkowski
Associate Professors Emeriti: J. Richard Harrison, Jane Salk, David J. Springate
Visiting Professor: Emily Choi
Clinical Professors: John Barden, Britt Berrett, Abhijit Biswas, Shawn Carraher, Larry Chasteen, Paul Convery, Howard Dover, John Gamino, Randall S. Guttery, William Hefley, Robert Hicks, Marilyn Kaplan, Sonia Leach, Peter Lewin, Jeffrey Manzi, John F. McCracken, Diane S. McNulty, Divakar Rajamani, Daniel Rajaratnam, Kannan Ramanathan, Mark Thouin, McClain Watson, Jeff Weekley, Habte Woldu, Fang Wu, Laurie L. Ziegler
Clinical Associate Professors: Shawn Alborz, Dawn Owens, Carolyn Reichert, Avanti P. Sethi, Ramesh Subramoniam, Aysegul Toptal, David Widdifield
Clinical Assistant Professors: Athena Alimirzaei, Christina (Krysta) Betanzos, Moran Blueshtein, Jerome Gafford, Jeffery (Jeff) Hicks, Revansiddha Khanapure, Kristen Lawson, Liping Ma, Ravi Narayan, Parneet Pahwa, Jason Parker, Nassim Sohaee
Professors of Instruction: Semiramis Amirpour, Mary Beth Goodrich, Chris Linsteadt, Matt Polze, Luell (Lou) Thompson
Associate Professors of Instruction: Vivek Arora, Judd Bradbury, Monica E. Brussolo, Amal El-Ashmawi, Ayfer Gurun, Maria Hasenhuttl, Julie Haworth, Thomas (Tom) Henderson, Jennifer G. Johnson, Kathryn Lookadoo, Sarah Moore, Mohammad Naseri Taheri, Hubert Zydorek
Assistant Professors of Instruction: Negin Enayaty Ahangar, Joseph Mauriello, Victoria D. McCrady, Rasoul Ramezani, Gaurav Shekhar
Professors of Practice: Gregory Ballew, Tiffany A. Bortz, Ranavir Bose, Alexander Edsel, Rajiv Shah
Associate Professors of Practice: Richard Bowen, Jackie Kimzey, David Parks, Margaret Smallwood, Steven Solcher, Kathy Zolton
Assistant Professors of Practice: Khatereh Ahadi, Steven Haynes, Abu Naser Islam, Edward Meda, Paul Nichols, Timothy Stephens, Guido Tirone, Robert Wright
Senior Lecturer: Juliann Chapman
Degree Requirements
The Master of Science in Business Analytics (MS BUAN) is a 36 semester credit hours STEM (Science, Technology, Engineering and Mathematics) degree program that provides students with a broad foundation in the business analytics and data science area. The program prepares students for professions in data science, big data, and analytics space. The core courses are designed to provide the foundation of tools and techniques to be used in the analytics domain whereas the electives allow for business application of the core techniques in Accounting, Finance, Cybersecurity, Healthcare, IT, Marketing, Social Media, and Operations. The program provides three options:
(1) The Flex Program allows students the flexibility to complete the program at their own pace and tailor their degree in preparation for specific career goals by selecting electives from various fields, including Accounting, Cybersecurity, Data Engineering, Data Science, Finance, Healthcare, IT, Marketing, Social Media, Operations. The purpose of the program is to equip students with the technical tools and professional communication skills needed to practice in business analytics. Multiple elective tracks are offered in the Flex Program. Admission to the program occurs in Fall, Spring, and Summer semesters.
(2) The Cohort Program is a two-year program in which students take all courses together as a cohort. It is designed for students from various backgrounds to gain knowledge to pursue opportunities in business analytics. The purpose of the program is to develop effective leaders in business analytics. Students may complete the Accounting Analytics track or the Data Science track. The Accounting Analytics track is offered in a face-to-face Cohort Program on campus, while the Data Science track may be completed in either a face-to-face Cohort Program on campus or an Online Cohort program. Special tuition, fees, and admissions requirements apply and the program is supported entirely by participant tuition/fees. Admission to the program occurs in Fall, Spring, and Summer semesters.
(3) The Online Program allows students the flexibility to complete the program completely online at their own pace, and tailor their degree in preparation for specific career goals by selecting electives from the Data Science track. The purpose of the program is to equip students with the technical tools and professional communication skills needed to practice in business analytics. Admission to the program occurs in Fall, Spring, and Summer semesters.
To apply for this degree program, an undergraduate degree is required (all majors are considered). Students must maintain a 3.0 grade-point average (GPA) in both core courses and in all graduate courses taken in the degree program, excluding program prerequisites to qualify for the MS degree.
Prerequisites
Students pursuing the Master of Science in Business Analytics degree program are required to fulfill one semester credit hour of MAS 6102 Professional Development course. In addition, knowledge of calculus is required and students who have not completed an undergraduate calculus course may satisfy the prerequisite by completing OPRE 6303 Quantitative Foundations of Business. Degree credit is not earned for program prerequisites, however, the grade achieved in prerequisites will count toward the student's grade-point average (GPA). All program prerequisites must be satisfied within the first semester of graduate study as a degree-seeking student.
Course Requirements
Core Courses: 18 semester credit hours
BUAN 6312 Applied Econometrics and Time Series Analysis
BUAN 6320 Database Foundations for Business Analytics
BUAN 6324 Business Analytics With SAS
or BUAN 6356 Business Analytics With R
or BUAN 6383 Modeling for Business Analytics
BUAN 6337 Predictive Analytics for Data Science
BUAN 6398 Prescriptive Analytics
BUAN 6359 Advanced Statistics for Data Science
Elective Courses: 18 semester credit hours
Students may choose any course with a BUAN prefix, excluding BUAN core courses, or any course from one or more tracks in the following areas to obtain in-depth knowledge in a specific industry domain. As part of the 18 semester credit hours of elective courses, students may also substitute up to six semester credit hours of any master's-level courses offered within JSOM as free electives, except for MIS 6320 or MIS 6326 or ACCT 6320 or OPRE 6393. Additionally, students must abide by any restriction specified in a course description.
BUAN 6009 Business Analytics Internship (Required Elective)1
Accounting Analytics Track
ACCT 6301 Financial Accounting
or ACCT 6330 Intermediate Financial Accounting I
BUAN 6311 Robotics and Financial Technology
ACCT 6336 Information Technology Audit and Risk Management
ACCT 6343 Accounting Information Systems
ACCT 6344 Financial Statement Analysis
or ACCT 6332 Intermediate Financial Accounting II
ACCT 6374 Advanced Data Analytics for Accountants and Auditors
ACCT 6384 Analytical Reviews Using Audit Software
or ACCT 6334 Auditing
ACCT 6386 Governance, Risk Management and Compliance (GRC)
Cybersecurity Analytics Track
BUAN 6368 Applied Cybersecurity Analytics and Risk Management
MIS 6316 Data Communications
MIS 6330 Cybersecurity Fundamentals
MIS 6333 Digital Forensics and Incident Management
MIS 6337 Information Technology Audit and Risk Management
MIS 6384 Preparing for Cybersecurity Threats
Data Engineering Track
BUAN 6340 Programming for Data Science
BUAN 6345 SAP Analytics
BUAN 6346 Big Data
BUAN 6347 Advanced Big Data Analytics
BUAN 6358 AWS Cloud Analytics
BUAN 6385 Robotic Process Automation
MIS 6309 Business Data Warehousing
MIS 6363 Cloud Computing Fundamentals
MIS 6389 AWS Cloud Solution Architecture
Data Science Track
BUAN 6311 Robotics and Financial Technology
BUAN 6333 Foundations of Programming for Business Analytics
BUAN 6335 Organizing for Business Analytics Platforms
BUAN 6340 Programming for Data Science
BUAN 6341 Applied Machine Learning
BUAN 6342 Applied Natural Language Processing
BUAN 6346 Big Data
BUAN 6357 Advanced Business Analytics With R
BUAN 6383 Modeling for Business Analytics
BUAN 6382 Applied Deep Learning
BUAN 6385 Robotic Process Automation
BUAN 6392 Causal Analytics and A/B Testing
MIS 6380 Data Visualization
Decisions and Operations Analytics Track
BUAN 6385 Robotic Process Automation
MIS 6398 Blockchain Technology and Applications
OPRE 6302 Operations Management
OPRE 6304 Operations Analytics
OPRE 6332 Spreadsheet Modeling and Analytics
OPRE 6335 Risk and Decision Analysis
OPRE 6377 Demand and Revenue Analytics
OPRE 6378 Supply Chain Strategy
Enterprise Systems Analytics Track
BUAN 6345 SAP Analytics
BUAN 6386 SAP Cloud Analytics
MIS 6319 Intelligent Enterprise Systems with SAP
MIS 6309 Business Data Warehousing
MIS 6332 Intelligent Enterprise Systems Configurations and Implementation with SAP
MIS 6369 Supply Chain Software with SAP
Financial Analytics Track
ACCT 6301 Financial Accounting
FIN 6301 Financial Management
FIN 6307 Mathematical Methods for Finance
FIN 6352 Financial Modeling For Valuation
FIN 6353 Financial Modeling for Investment Analysis
FIN 6360 Derivatives Markets
FIN 6368 Financial Information and Analysis
FIN 6382 Financial Applications and Statistical Methods
FIN 6392 Financial Technology and Blockchain
MIS 6398 Blockchain Technology and Applications
Healthcare Analytics Track
HMGT 6320 The American Healthcare System
HMGT 6323 Healthcare Informatics
HMGT 6325 Healthcare Operations Management
HMGT 6327 Electronic Health Records Applications
HMGT 6334 Healthcare Analytics
BUAN 6335 Organizing for Business Analytics Platforms
Marketing Analytics Track
BUAN 6392 Causal Analytics and A/B Testing
MKT 6301 Marketing Management
MKT 6309 Marketing Data Analysis and Research
MKT 6336 Pricing Analytics
MKT 6343 Social Media Marketing and Insights
MKT 6345 Quantitative Marketing Decision-Making
MKT 6347 Marketing Analytics Project
MKT 6349 MarTech Ecosystem
MKT 6352 Marketing Web Analytics and Insights
MKT 6353 Customer Analytics and Insights
MKT 6384 Advanced Marketing Web Analytics and Insights
Social Media Analytics Track
BUAN 6335 Organizing for Business Analytics Platforms
BUAN 6340 Programming for Data Science
BUAN 6341 Applied Machine Learning
BUAN 6344 Web Analytics
BUAN 6392 Causal Analytics and A/B Testing
MIS 6334 Advanced Business Analytics with SAS
MIS 6373 Social Media Business
MIS 6378 Customer Relationship Management with Salesforce
MIS 6380 Data Visualization
Graduate Certificate in Applied Machine Learning
12 semester credit hours
Faculty
Overview
The Graduate Certificate in Applied Machine Learning comprises courses that teach statistics geared towards data science needs, and important concepts in business analytics, machine learning and natural language processing necessary for business applications.
Students pursuing this certificate will be exposed to:
- Statistical methods to analyze data from observational studies and experimental designs, and to communicate relevant findings to a business audience.
- Approaches that extract actionable intelligence from firms' business data for various applications, including (but not limited to) customer segmentation, customer relationship management (CRM), personalization, online recommendation systems, web mining, and product assortment.
- Machine learning approaches focused on applications to business data, like approaches for text mining, non-linear regression models, resampling methods, neural networks, etc..
- Natural language processing and related approaches that help gain actionable insights in real-world applications (for example, through the analysis and interpretation of language in the contexts of social media and business text/unstructured data).
Required courses: 12 semester credit hours
BUAN 6341 Applied Machine Learning
BUAN 6356 Business Analytics with R
BUAN 6359 Advanced Statistics for Data Science
Choose one course from the following:
BUAN 6342 Applied Natural Language Processing
BUAN 6382 Applied Deep Learning
1. Students may use BUAN 6009 only for their first internship and any additional internship must be completed as BUAN 6V98 (3 semester credit hours maximum). Students may use BUAN 6V98 or BUAN 6390 to fulfill the internship requirement. Students are no longer eligible to enroll in BUAN 6009 if they have already completed BUAN 6V98 or BUAN 6390.