MSBA Practicum & BSBA Capstone Projects
MSBA Practicum & BSBA Capstone Projects

MSBA Practicum & BSBA Capstone Projects

 

 

The MSBA practicum and BSBA capstone projects are designed to apply analytics knowledge gained in the classroom to real-world problems.

In these one-semester courses, students work in teams on a sponsor’s project to receive academic credits. External industry sponsors propose the project and work closely with the students over the semester.

How It Works

GW School of Business students conduct a pro-bono project proposed by an industry sponsor. With the help of their industry sponsor and GW faculty mentors, students embark on a full-cycle data analytics project using tools provided by GW and the sponsor. Projects are often based on mock data or publicly available data; students do not need access to proprietary information. Teams of several students are matched to accepted projects, and the industry sponsors meet with the team and provide guidance and feedback for the duration of the project.

These projects are not official internships. Some project sponsors require students to sign non-disclosure agreements (NDAs). In some projects, software licenses or use of premium cloud-based software may be required to conduct in-depth analysis, create complex models, etc. Any costs incurred will be presented to sponsors as a budget before work begins.

How Sponsorship Benefits Your Company

These projects offer:

  • The opportunity for companies to look at a problem from a fresh perspective.
  • Access to a small team of junior-level data scientists and developers to prototype a working solution to that problem.
  • The right to utilize any work product or IP developed by the student team through the project.
  • Volunteer or professional development opportunities for sponsor mentors.
Acceptance Criteria for Sponsorship

Submitted projects are assessed for feasibility and quality. 

  • Positive considerations for feasibility include:
    • Use of public data, or data that is stored and controlled by the sponsor with access provided to students. 
    • Use of standard computing technologies, or specialized computing technology that is provided by the sponsor. 
    • Medium complexity and difficulty levels that challenge a student group, but are realistically achievable in the course of a semester. 
    • Exposure to novel technologies and approaches. 
  • Positive considerations for quality include:
    • Polished proposals. 
    • Proposals that align with industry standards or best practices. 
    • Proposals that align with ethical and responsible AI practices.
Learning Objectives for Students

After completing these projects, students will be able to demonstrate the following abilities:

  • Design, develop, and execute a data-driven investigation or prototype.
  • Frame a data-driven study based on a client’s requirements and the available data.
  • Identify the value proposition for a project and the appropriate questions that will inform progress.
  • Document and describe the trade-offs involving the data or technology, its quality and availability, depth of analysis, and available resources.
  • Convey project deliverables in different modes — one for academic requirements and one for project sponsor.
Student Responsibilities
  • Engage in regular sessions with the sponsor to thoroughly understand scope of work, including (but not limited to): clarifying specific project requirements, gathering feedback, and discussing progress and any challenges.
  • If and when the sponsor introduces new topics, methodologies and/or technologies, students must conduct their own research to enhance their understanding.
  • In challenging situations, students must work collaboratively with the sponsor and make use of any academic resources available to them.
  • Students are expected to maintain a high level of professionalism throughout the project.
  • At the conclusion of the project, each team is required to submit a deliverable based on the sponsors’ requirements.

 

 

Submit a Fall 2024 Project Proposal

Project sponsor proposals are due by Friday, August 16, 2024. Acceptance decisions will be announced by Friday, August 23.

Propose a Project

 

 

 

Explore Our Fall 2023 MSBA Practicum Projects

 

The 2023 Fall Analytics Practicum included 12 sponsoring organizations, 13 student projects, and 54 graduate and undergraduate students. Sponsors ranged from some of the largest banks and professional services companies in the world to specialized software providers and D.C.-based contractors and consultants.

Practicum projects focused on timely and meaningful topics such as:

  • Analysis of telehealth services and social determinants of health
  • Auditing LLM systems
  • Building AI-based chatbots
  • Climate change resiliency
  • COVID-19 impacts on nursing homes
  • Cybersecurity analytics
  • Financial fraud detection
  • LLM applications in consumer finance
  • Sales forecasting
  • Strategic data management initiatives
  • Tracking and risk-scoring large cargo ships

Nine out of 13 organizations expressed a strong interest in sponsoring again in the future, and three out of 13 organizations noted some interest in sponsoring in future semesters. See below for additional details relating to the 13 projects.

 

FI Consulting logo
 
Fall 2023 MSBA Practicum group 1
 

Social Determinants of Health and Access to Credit Impact on Life Expectancy

Congratulations to Danyu Z., Yachen Wu (Kendall Wu), Rodrigo R. Jaar and Swapnil Duggal on an exceptional project with FI Consulting focusing on the impact of social determinants of health and access to credit on life expectancy. The group used open tools like Python, PiML, and Neo4j to train explainable regression and graphical models for complex health issues.

Project sponsor: FI Consulting

Learn more about this project

 

MITRE logo
Fall 2023 MSBA Practicum group 2

 

 

Understanding Climate Resiliency in the Agricultural Supply Chain

Congratulations to Mallika Y., Salaah Khan, Xinyu (Cindy) Duan, and John Zhang (Yuqi Zhang) on their successful project with Mitre focusing on understanding climate resiliency in the agricultural supply chain. Their innovative agent-based modeling approach provided valuable insights into how extreme weather events impact the agricultural supply chain with a focus on Florida's citrus fruit sector. This team used tools like rstats, The AnyLogic Company, Excel, and other data analytics software to model the effects of climate change on agriculture in the region.

Project sponsor: Mitre

Learn more about this project

 

Relativity logo
Fall 2023 MSBA Practicum group 3

 

 

Adversarial Analysis of Large Language Model (LLM) Applications

Congratulations to Priyanka Bhatia, Ben Wehrley and Xiaosong (Frank) Yao on a great project with Relativity focusing on adversarial analysis of large language model applications in legal tech. Their red-teaming approach exposed potential data leaks between ChatGPT sessions and other risks.

Project sponsor: Relativity

Learn more about this project

 

Wells Fargo logo
Fall 2023 MSBA Practicum group 4

 

 

Generating Datasets for Validating Complaint-classification Natural Language Processing
(NLP) Models

Congratulations to Kathleen McQuiddy, Joon Kyu Hong, Stephanie Palanca, and Ian Kang for their impactful project with Wells Fargo working with large language models to develop synthetic complaint datasets to enhance accuracy in classifying customer complaints, a key step forward in enhancing customer experience. They also used statistical quality control approaches to measure the reliability of their approach.

Project sponsor: Wells Fargo

Learn more about this project

 

World WildLife Fund logo
Fall 2023 MSBA Practicum group 5

 

 

WWF Fact-Based AI Chatbot

Congratulations to Zhipeng Zhao, Pranjal Shukla, Wenxuan Xue, and Saloni Sharma on their successful AI chatbot project with the World WildLife Fund leveraging large language models and natural language processing to develop a prototype chatbot to enhance search on WWF’s website.

Project sponsor: The World WildLife Fund

Learn more about this project

 

Niyam IT logo
Fall 2023 MSBA Practicum group 6

 

 

Data Visualization and Detecting Anomalies in Paycheck Protection Program (PPP) Loan Data

Congratulations to Pavneet Singh, Rose Hemans, Kaixuan Han, and Bagya Widanagamage for their impactful project with Niyam IT on data visualization and anomaly detection in federal payroll protection loan data. This team tackled the challenge of identifying potential fraud in loan applications using open source Python tools and presented their results on GitHub.

Project sponsor: Niyam IT

Learn more about this project

 

MITRE logo
Fall 2023 MSBA Practicum group 7

 

 

Exploring the Use of Ontologies for Business Analytics

Congratulations to Sibeso Mubonda, Wanting Liu, Lejla Skahic, and Stephen Gaffney for their insightful work with Mitre on exploring the use of ontologies for business analytics. A major issue in AI today is the use of available data versus appropriate data. This project built a proof of concept for using ontologies to drive data collection that is aligned to an organization's goals and strategies, potentially enhancing data integration and decision-making in various business domains.

Project sponsor: Mitre

Learn more about this project

 

Gainwell logo
Fall 2023 MSBA Practicum group 8

 

 

Soniat Analytics

Congratulations to Nigel Nyajeka, Xinyi Li, Prachi Pathak, and Gaurav Sethi on their insightful project with alum Justin Soniat and Gainwell Technologies. The team analyzed CMS COVID-19 data, uncovering insights on the pandemic's deadly impact across nursing homes in various states and regions using descriptive statistics, linear models, decision trees and clustering in R, Python and Tableau.

Project sponsor: Gainwell Technologies

Learn more about this project

 

Deloitte logo
Fall 2023 MSBA Practicum group 9

 

 

Cyber Threat Recon

Congratulations to Emmanuel Asong, Dimple Modi, Bernard Low, and Rachelle Azulay on their successful cybersecurity project with Deloitte developing AI-driven cyber threat analytics for the Department of Defense. The team used unsupervised machine learning to summarize and cluster data breaches, informing strategic responses.

Project sponsor: Deloitte

Learn more about this project

 

Bolt logo
Fall 2023 MSBA Practicum group 10

 

 

Accenture logo
Fall 2023 MSBA Practicum group 11

 

 

Agricultural Bank of China logo
Fall 2023 MSBA Practicum group 12

 

 

Ship Explorer

Congratulations to Theodoros Pateros, Yeobeen Yun, Fang (Eric) Tien, and Salem Addisu at the helm of their successful Ship Explorer project with Agricultural Bank of China New York. This team developed a cloud-based tool to enhance shipping transparency and combat illegal activities. Utilizing big transactional datasets, Python and SQL, they engineered a solution to track ship movements and assess compliance risk, visualized through an interactive web interface.

Project sponsor: Agricultural Bank of China - New York

Learn more about this project

 

 
Fall 2023 MSBA Practicum group 13

 

 

Explore Our Spring 2023 MSBA Practicum Projects

The Spring 2023 Analytics Practicum included 10 sponsoring organizations and 58 graduate and undergraduate students. Sponsors ranged from some of the largest banks and professional services companies in the world to cutting-edge startups and specialized D.C.-based contractors and consultants.

Practicum projects focused on timely and meaningful topics such as:

  • Training robust machine learning models for credit scoring
  • Bias testing and remediation for machine learning models
  • Machine learning for compliance tasks
  • Building chatbots
  • Cybersecurity
  • Auditing chatbots for harmful outputs and hidden biases
  • Greenhouse gas emission tracking and analysis

 

Agricultural Bank of China logo
MSBA 2023 practicum projects, group 1 (sponsored by the Agricultural Bank of China)

 

 

Deloitte logo
MSBA 2023 practicum projects, group 2 (sponsored by Deloitte)

 

 

FI Consulting logo
MSBA 2023 practicum group 3 (sponsored by FI Consulting)

 

 

MicroStrategy logo
MSBA 2023 practicum group 4 (sponsored by MicroStrategy)

 

 

MITRE logo
MSBA 2023 practicum group 5 (sponsored by MITRE)

 

 

Navanti Group logo
MSBA 2023 practicum group 6 (sponsored by the Navanti Group)

 

 

Relativity logo
MSBA 2023 practicum group 7 (sponsored by Relativity)

 

 

SolasAI logo
MSBA 2023 practicum group 8 (sponsored by SolasAI)

 

 

Wells Fargo logo
MSBA 2023 practicum group 9 (sponsored by Wells Fargo)

 

 

Training Credit Models with the PiML Package

Students trained and evaluated several inherently explainable machine learning models, tested their outcomes for systemic bias, conducted bias remediation, and wrote a model card. They used the PiML Python package for the entire project. The model card and Google Colab notebook are available for other aspiring credit analysts and model validators.

Project sponsor: Wells Fargo

Group members: Bader Albaarrak, Jialiang Chen, Taria Herbert, Runtong Jiang, Pranita Shetty and Le Zhang

Learn more about this project

 

World WildLife Fund logo
MSBA 2023 practicum group 10 (sponsored by the World WildLife Fund)