Complete all courses and requirements listed below unless otherwise indicated. 

Core Requirements

IE 6400Foundations for Data Analytics Engineering4
IE 6600Computation and Visualization for Analytics4
IE 6700Data Management for Analytics4
IE 7275Data Mining in Engineering4
IE 7615Neural Networks and Deep Learning4

Options

Complete one of the following options:

Project Option

IE 7945Master’s Project4
Complete 8 semester hours from the elective course list below.8

Thesis Option 1

Complete the following course twice:8
Thesis
Complete 4 semester hours from the elective course list below.4
In addition to completing the thesis course, students must successfully complete the thesis submission process, including securing committee and Graduate School of Engineering signatures and submission of an electronic copy of their MS thesis to ProQuest.

Optional Co-op Experience

Complete the following. Students must complete ENCP 6100 to qualify for co-op experience:
ENCP 6100Introduction to Cooperative Education1
ENCP 6964Co-op Work Experience0
or ENCP 6954 Co-op Work Experience - Half-Time
or ENCP 6955 Co-op Work Experience Abroad - Half-Time
or ENCP 6965 Co-op Work Experience Abroad

Elective Course List  

Any course in the following list will serve as an elective course, provided the course is offered and the student satisfied prerequisites and program requirements. 

Foundations of Artificial Intelligence
Artificial Intelligence for Human-Computer Interaction
Reinforcement Learning and Sequential Decision Making
Pattern Recognition and Computer Vision
Large-Scale Parallel Data Processing
Fundamentals of Cloud Computing
Principles of Scalable Data Management: Theory, Algorithms, and Database Systems
Big-Data Systems and Intelligence Analytics
Big Data Architecture and Governance
Parallel Processing for Data Analytics
Fundamentals of Computer Engineering
Engineering Project Management
Economic Decision Making
Financial Management for Engineers
Computational Modeling in Industrial Engineering
Mathematics for Machine Learning
Special Topics in Industrial Engineering
Structured Data Analytics for Industrial Engineering
Healthcare Systems Modeling and Analysis
Biosensor and Human Behavior Measurement
Data Mining for Engineering Applications
Manufacturing Systems Design
Data Warehousing and Integration
Supply Chain Engineering
Simulation Analysis
Statistical Methods in Engineering
Statistical Quality Control
Reliability Analysis and Risk Assessment
Applied Reinforcement Learning in Engineering
Statistical Learning for Engineering
Special Topics in Industrial Engineering
Applied Natural Language Processing in Engineering
Business Analysis and Information Engineering
Business Process Engineering
Mathematical Methods for Mechanical Engineers 1
Deterministic Operations Research
Probabilistic Operation Research
Inventory Theory
Integer and Nonlinear Optimization
Network Analysis and Advanced Optimization
Logistics, Warehousing, and Scheduling

Program Credit/GPA Requirements

32 total semester hours required (33 with optional co-op)
Minimum 3.000 GPA required

1

A thesis is required for all students who receive financial support from the university in the form of a research, teaching, or tuition assistantship. The thesis topic should cover one or more of the areas from statistics, mathematics, optimization, data mining, machine learning, database design, Big Data, visualization tools, or forecasting methods. The thesis should train students for research in data and operations analytics and/or prepare them for a doctoral program.