CIS511: Causal Inference
This is a course about causality theory and causal inference techniques.
We begin with classical paradoxes and explain why causality is fundamentally different from statistics.
We then compare Pearl's structural causal model with Rubin's potential outcome approach.
Once the rigorous languages to think about causality are introduced, we dive into various causal inference techniques.
We first discuss the back-door and front-door criteria which pave the way for the more general technique of do-calculus.
Then, we analyze the challenge of mediation in the context of discrimination study.
The second part of the course covers commonly used causal inference techniques (e.g., matching, instrumental variable, difference-in-differences, regression discontinuity) with an emphasis on the underlying causal assumptions. Students are expected to be familiar with (ideally measure-theoretical) probability theory because of the extensive use of mathematical proofs in this course. The course does not cover software tools for causal inference.
Created by Huaxia Rui on 2025-04-26
MSM504: Probability Theory (Open Access)
This is a PhD level course on probability theory. We first review integration theory before laying out the measure-theoretic foundation of probability theory. We then introduce important concepts and tools that deal with a sequence or a series of random variables. We finish MSM504 with the modern theory of conditional expectation/distribution/independence which are important for causal inference.
Created by Huaxia Rui on 2025-04-26
MSM505: Stochastic Process (Open Access)
This is a PhD level course on stochastic process. We introduce the general concepts and
properties of (mostly discrete-time) stochastic processes which lays the foundation for more
detailed studies of various types of stochastic processes encountered in business research. We
will focus on the classical renewal theory and Markov chain theory. Towards the end, we
unify them in the framework of Markov renewal theory. We will spend the last week or two
to discuss applications, with a particular emphasis on Markov decision process.
Created by Huaxia Rui on 2025-04-26
GBA411: Business Modeling
The course is structured in three parts. In the first part you will learn how
to model business decision problems in a structured way using spreadsheets. In the second part,
you will learn how to use the computer to solve complex decision problems involving many variables
and constraints. In the third part, you will learn Monte Carlo simulation so that you will have a
framework for understanding and analyzing uncertainty in business.
Created by Huaxia Rui on 2025-04-26
CIS434: Social Media Analytics
The rise of social media has fundamentally changed many aspects of business by empowering customers and the general public in an unprecedented way. They are well connected with each other through platforms like Facebook and X, and they can easily express and distribute their comments, criticisms, or endorsements publicly to large audiences in real time. This media revolution not only forces companies to actively manage their presence and engage with customers on social media platforms but also offers them a golden opportunity to extract intelligence from the vast amount of unstructured data. Technology and strategies are increasingly intertwined in this new frontier of innovation and competition.
This course draws on a unique blend of social media strategies and the rapidly expanding supporting technologies.
Created by Huaxia Rui on 2025-06-07
CIS438: Agentic AI Applications
This course introduces the basics of developing web-based Agentic AI applications, with three objectives. The primary objective is to introduce the design of agentic AI applications. The second objective is to prepare students for projects that require not only the analysis of data or the use of modern AI techniques, but also the illustration of analytics and AI functionalities through a web application. The third objective is to pave the way for subsequent courses so that students can use what they learn in this course to create a web application for what they learn in other analytics courses.
Created by Huaxia Rui on 2026-01-16
GBA411: Business Modeling
The course is structured in three parts. In the first part you will learn how
to model business decision problems in a structured way using spreadsheets. In the second part,
you will learn how to use the computer to solve complex decision problems involving many variables
and constraints. In the third part, you will learn Monte Carlo simulation so that you will have a
framework for understanding and analyzing uncertainty in business.
Created by Huaxia Rui on 2025-04-26
CIS434: Social Media Analytics
The rise of social media has fundamentally changed many aspects of business by empowering customers and the general public in an unprecedented way. They are well connected with each other through platforms like Facebook and X, and they can easily express and distribute their comments, criticisms, or endorsements publicly to large audiences in real time. This media revolution not only forces companies to actively manage their presence and engage with customers on social media platforms but also offers them a golden opportunity to extract intelligence from the vast amount of unstructured data. Technology and strategies are increasingly intertwined in this new frontier of innovation and competition.
This course draws on a unique blend of social media strategies and the rapidly expanding supporting technologies.
Created by Huaxia Rui on 2025-06-07
CIS438: Agentic AI Applications
This course introduces the basics of developing web-based Agentic AI applications, with three objectives. The primary objective is to introduce the design of agentic AI applications. The second objective is to prepare students for projects that require not only the analysis of data or the use of modern AI techniques, but also the illustration of analytics and AI functionalities through a web application. The third objective is to pave the way for subsequent courses so that students can use what they learn in this course to create a web application for what they learn in other analytics courses.
Created by Huaxia Rui on 2026-01-16
CIS433: AI and Deep Learning
Artificial intelligence (AI) was born in the middle of the 20th century as a branch of computer science. Early development of the discipline was dominated by the paradigm of symbolic AI, emphasizing reasoning and knowledge representation. However, since the 1990s, significant progress has been made in the subfield of machine learning. The breakthrough in artificial neural networks, rebranded as deep learning, represents the state-of-the-art of machine learning in many tasks, including computer vision and natural language processing. This has in turn triggered a burst of enthusiasm and leads to huge investment in AI in the business world as well as in society at large. This course introduces the field of AI to students with a particular emphasis on deep learning which is driving the current AI revolution. The course consists of four modules. The first module establishes the foundation of AI and deep learning and introduces the main tools for this course. The second module focuses on deep learning architectures for the understanding and generation of images. The third module focuses on architectures designed for sequence data, with a particular focus on the transformer architecture which has revolutionized the field of natural language processing since its release in 2017. The fourth module introduces large language models (LLM) and techniques for fine-tuning foundation models. The course emphasizes experiential learning and contains many hands-on projects using PyTorch and TensorFlow/Keras.
Created by Huaxia Rui on 2025-03-02
CIS434: Social Media Analytics
The rise of social media has fundamentally changed many aspects of business by empowering customers and the general public in an unprecedented way. They are well connected with each other through platforms like Facebook and X, and they can easily express and distribute their comments, criticisms, or endorsements publicly to large audiences in real time. This media revolution not only forces companies to actively manage their presence and engage with customers on social media platforms but also offers them a golden opportunity to extract intelligence from the vast amount of unstructured data. Technology and strategies are increasingly intertwined in this new frontier of innovation and competition.
This course draws on a unique blend of social media strategies and the rapidly expanding supporting technologies.
Created by Huaxia Rui on 2025-06-07
CIS438: Agentic AI Applications
This course introduces the basics of developing web-based Agentic AI applications, with three objectives. The primary objective is to introduce the design of agentic AI applications. The second objective is to prepare students for projects that require not only the analysis of data or the use of modern AI techniques, but also the illustration of analytics and AI functionalities through a web application. The third objective is to pave the way for subsequent courses so that students can use what they learn in this course to create a web application for what they learn in other analytics courses.
Created by Huaxia Rui on 2026-01-16
ITTW2025: IT Teaching Workshop 2025 (Open Access)
Repository of slides from 2025 IT Teaching Workshop, hosted by University of Delaware. Source: https://sites.udel.edu/it-teaching-workshop/
Created by Huaxia Rui on 2025-05-17
ITTW2021: IT Teaching Workshop 2021 (Open Access)
Repository of slides from 2021 IT Teaching Workshop, hosted by Georgia Tech (virtual).
Source: https://simon.rochester.edu/simon-events/2021-it-teaching-workshop
Created by Natural Stupidity on 2025-05-06
ITTW2024: IT Teaching Workshop 2024 (Open Access)
This is a repository of teaching materials shared by participants of the 2024 IT Teaching Workshop hosted by UT Austin.
Created by Huaxia Rui on 2025-05-07
ITTW2023: IT Teaching Workshop 2023 (Open Access)
Repository of slides from 2023 IT Teaching Workshop, hosted by Boston University.
Source: https://www.bu.edu/dbi/events/it-teaching-workshop/
Created by Natural Stupidity on 2025-05-06
ITTW2019: IT Teaching Workshop 2019 (Open Access)
This is a repository of teaching materials shared by participants of the 2019 IT Teaching Workshop hosted by Wharton. Source: https://simon.rochester.edu/simon-events/2019-it-teaching-workshop
Created by Huaxia Rui on 2025-05-11