APPM 4720 - Open Topics in Applied Mathematics
Primary Instructor
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Fall 2023
Provides a vehicle for the development and presentation of new topics that may be incorporated into the core courses in applied mathematics. Department enforced prerequisite: variable, depending on the topic, see instructor. May be repeated up to 15 total credit hours. Same as APPM 5720.
APPM 5720 - Open Topics in Applied Mathematics
Primary Instructor
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Fall 2023
Provides a vehicle for the development and presentation of new topics that may be incorporated into the core courses in applied mathematics. Department enforced prerequisite: variable, depending on the topic, see instructor. May be repeated up to 6 total credit hours. Same as APPM 4720.
BADM 4830 - Special Topics
Primary Instructor
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Spring 2021 / Fall 2021
Various topics in business and society drawing from a variety of business disciplines.
BAIM 4200 - Fundamentals of Machine Learning: Data-Driven Decision-Making
Primary Instructor
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Fall 2022
Students in this class will use the Python programming language to create, evaluate, and deploy advanced machine learning predictive models. They will be trained in using modern collaborative source-code versioning tools. Best-practice methods will be provided to develop and create machine learning models, enabling their coding processes and their output to be shared with other analysts and managers alike. Formerly MGMT 4500.
ORGN 4210 - Thinking with Artificial Intelligence
Primary Instructor
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Spring 2026
In this hands-on course, students learn to think and act systematically alongside artificial intelligence. Using systems thinking principles, they explore how AI tools can analyze, design, and execute business solutions. Students learn to break down complex problems, identify where AI adds value, and apply advanced tools to real-world challenges. The course culminates in a capstone project where each student builds an AI-powered �one-person venture,� demonstrating how human creativity, machine intelligence, and systems thinking combine to drive rapid innovation and strategic decision-making. Formerly BAIM 4210.
STAT 4350 - Applied Deep Learning 1
Primary Instructor
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Fall 2024 / Spring 2025 / Fall 2025 / Spring 2026
Introduces students to state-of-the-art deep learning techniques employed in the industry. This course will focus on training neural networks and computer vision, including image classification and transformation, object detection, and facial recognition. Advanced topics will include domain adaptation and learning techniques. There will be an emphasis on reading current literature. Recommended prerequisite: knowledge of Python is required, and familiarity with TensorFlow and PyTorch is a plus but is not a requirement. Same as STAT 5350.
STAT 4360 - Applied Deep Learning 2
Primary Instructor
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Spring 2024
Introduces students to state-of-the-art deep learning techniques employed in the industry. This course will focus on natural language processing, multimodal learning, generative and graph neural networks, speech and music recognition, and reinforcement learning. Students will learn software engineering techniques using Python. There will be an emphasis on reading current literature. Same as STAT 5360.
STAT 5350 - Applied Deep Learning 1
Primary Instructor
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Fall 2024 / Spring 2025 / Fall 2025 / Spring 2026
Introduces students to state-of-the-art deep learning techniques employed in the industry. This course will focus on training neural networks and computer vision, including image classification and transformation, object detection, and facial recognition. Advanced topics will include domain adaptation and learning techniques. There will be an emphasis on reading current literature. Recommended prerequisite:probability (equivalent to APPM 3570), statistics (equivalent to STAT 3400), some familiarity with numerical analysis, solid knowledge of Python, and familiarity with TensorFlow and PyTorch is a plus but is not a requirement. Same as STAT 4350.
STAT 5360 - Applied Deep Learning 2
Primary Instructor
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Spring 2024
Introduces students to state-of-the-art deep learning techniques employed in the industry. This course will focus on natural language processing, multimodal learning, generative and graph neural networks, speech and music recognition, and reinforcement learning. Students will learn software engineering techniques using Python. There will be an emphasis on reading current literature. Same as STAT 4360.
