UT Dallas 2021 Graduate Catalog

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, 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, Syam Menon, Vijay S. Mookerjee, B. P. S. Murthi, Vikram Nanda, Özalp Özer, Mike W. Peng, Hasan Pirkul, Suresh Radhakrishnan, Srinivasan Raghunathan, Ram C. Rao, Brian Ratchford, Michael J. Rebello, 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, Norris Bruce, Zhonglan Dai, Rebecca Files, Michael Hasler, Dorothée Honhon, Bin Hu, Kyle Hyndman, Surya N. Janakiraman, Robert L. Kieschnick Jr., Atanu Lahiri, Jun Li, Ningzhong Li, Maria Loumioti, Lívia Markóczy, Amit Mehra, Toyah Miller, Ramachandran (Ram) Natarajan, Naim Bugra Ozel, H. Dennis Park, Anyan Qi, Cuili Qian, Young U. Ryu, Gil Sadka, Harpreet Singh, David J. Springate, Upender Subramanian, Shaojie Tang, Kelsey D. Wei, Han (Victor) Xia, Yexiao Xu, Alejandro Zentner, Jieying Zhang, Yuan Zhang, Feng Zhao, Yibin Zhou

Assistant Professors: Khai Chiong, Emily Choi, Rafael Copat, Soraya Fatehi, Andrew Frazelle, Ying Huang, Joonhwi Joo, Sora Jun, Jason Kautz, Tongil Kim, Sheen Levine, Meng Li, Christopher Mace, Samir Mamadehussene, Jean-Marie Meier, Radha Mookerjee, Jedson Pinto, Ignacio Rios Uribe, Alejandro Rivera Mesias, Alessio Saretto, Simon Siegenthaler, Serdar Simsek, Kirti Sinha, Xiaoxiao Tang, Shervin Tehrani, Ashwin Venkataraman, Christian Von-Drathen, Guihua Wang, Hongchang Wang, Pingle Wang, Shouqiang Wang, Junfeng Wu, Steven Xiao, Yingjie Zhang, Zhe (James) Zhang

Professor Emeritus: John J. Wiorkowski

Associate Professors Emeriti: J. Richard Harrison, Jane Salk

Clinical Professors: John Barden, Britt Berrett, Abhijit Biswas, Pamela Foster Brady, Shawn Carraher, Larry Chasteen, Paul Convery, David Cordell, 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, David Ritchey, 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, James Szot, Aysegul Toptal, David Widdifield

Clinical Assistant Professors: Athena Alimirzaei, Christina (Krysta) Betanzos, Moran Blueshtein, Judd Bradbury, Sourav Chatterjee, Jerome Gafford, Ayfer Gurun, Jeffery (Jeff) Hicks, Revansiddha Khanapure, Kristen Lawson, Kathryn Lookadoo, Liping Ma, Sarah Moore, Ravi Narayan, Parneet Pahwa, Jason Parker, Drew Peabody, Nassim Sohaee

Professors of Instruction: Mary Beth Goodrich, Charles Hazzard, Chris Linsteadt, Luell (Lou) Thompson

Associate Professors of Instruction: Vivek Arora, Monica E. Brussolo, Amal El-Ashmawi, Maria Hasenhuttl, Jennifer G. Johnson, Hubert Zydorek

Assistant Professors of Instruction: Julie Haworth, 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, Scott Janke, Edward Meda, Timothy Stephens

Senior Lecturers: Semiramis Amirpour, Juliann Chapman, Negin Enayaty Ahangar, Thomas (Tom) Henderson, Joseph Mauriello, Robert (Stephen) Molina, Prithi Narasimhan, Mohammad Naseri Taheri, Paul Nichols, Matt Polze, Guido Tirone, Robert Wright

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. Following the completion of 18 credit hours, a student must successfully complete an internship or practicum.

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

BUAN 6337 Predictive Analytics Using SAS

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. Students may also substitute up to six semester credit hours master's-level courses from any unrestricted course/prefix offered within JSOM.

BUAN 6009 Business Analytics Internship (Required Elective)1

Accounting Analytics Track

ACCT 6301 Financial Accounting

or ACCT 6330 Intermediate Financial Accounting I

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 6384 Analytical Reviews Using Audit Software

or ACCT 6334 Auditing

ACCT 6386 Governance, Risk Management and Compliance (GRC)

Cybersecurity Analytics Track

MIS 6316 Data Communications

MIS 6330 Cybersecurity Fundamentals

MIS 6333 Digital Forensics and Incident Management

MIS 6337 Information Technology Audit and Risk Management

MIS 6343 Advanced Cybersecurity Management

MIS 6348 Digital Governance, Risk, and Compliance

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 6383 Advanced Data Management

MIS 6389 AWS Cloud Solution Architecture

Data Science Track

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 6382 Applied Deep Learning

BUAN 6385 Robotic Process Automation

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

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 Numerical and Statistical Methods in Finance

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

MKT 6301 Marketing Management

MKT 6309 Marketing Data Analysis and Research

MKT 6336 Pricing Analytics

MKT 6341 Marketing Automation and Campaign Management

MKT 6342 Marketing Customer Insights Development

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

Enterprise Systems Analytics Track

BUAN 6345 SAP Analytics

BUAN 6386 SAP Cloud Analytics

MIS 6319 Enterprise Resource Planning with SAP

MIS 6309 Business Data Warehousing

MIS 6332 ERP Configurations and Implementation with SAP

MIS 6369 Supply Chain Software with SAP

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:

  1. Statistical methods to analyze data from observational studies and experimental designs, and to communicate relevant findings to a business audience.
  2. 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.
  3. Machine learning approaches focused on applications to business data, like approaches for text mining, non-linear regression models, resampling methods, neural networks, etc..
  4. 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 6342 Applied Natural Language Processing

BUAN 6356 Business Analytics with R

BUAN 6359 Advanced Statistics for Data Science

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.

Updated: 2021-05-27 13:11:55 v15.33ba26