Sponsor a Project
The data science curriculum offered at the graduate (MS) and undergraduate (BA/BS) levels at the University of Rochester prepares students for the challenging task of deriving insight from vast quantities of structured and unstructured data in a variety of disciplines. At the core of the data science curriculum are the capstone and practicum courses for undergraduate and graduate students respectively. These semester-long courses emphasize a team-based learning experience that gives students the opportunity to conduct real-world analytics projects using data provided by sponsoring organizations.
Since the program was launched in 2016, over 35 projects from 20 companies have been offered to students, spanning a broad range of industry segments such as consumer retail, healthcare, agriculture, government and finance.
Each project begins with a presentation to students by a sponsor, highlighting the:
- Business need
- Goal of the data analytics effort
- Description of the available data
Students then work in teams of three to four members over an eight to ten week period (one semester) to understand the business problem, clean and analyze the data, and devise a solution. During the project, the students are strongly encouraged to establish and maintain regular communication with an assigned contact from the sponsoring entity. Day-to-day progress on the project is tracked by university faculty assigned to the course.
At the end of the project, students are expected to present and provide an executive summary of their findings to their sponsor.
Capstone and practicum course students have successfully completed a rigorous set of upper-level undergraduate or graduate level coursework in computational statistics, data mining, machine learning and computational tools in data science.
Capstone/Practicum Project Sponsorship
Interested in sponsoring a team project for an upcoming semester? Our students are ready to help you solve a challenging business problem using data analytics.
There is no sponsorship fee or funding required to sponsor a project. All we require is a challenging business problem and data for analysis. Data cannot include personally identifiable information (PII), and must be shared in a manner that is consistent with your organization's third-party data transfer governance rules.
Many of our previous sponsors have successfully anonymized business sensitive information in data sets and problem descriptions, while still maintaining the necessary technical information required for students to execute the project. We understand the time, effort and commitment required to sponsor a student project, and we are grateful to sponsoring organizations for their engagement.
- A well-defined problem statement that can be articulated in one or two concise paragraphs.
- A data set that can be accessed by the students, either as a flat file (e.g. CSV), or via remote access to the sponsor’s database/data warehouse using software tools made available to the students.
- A problem that requires statistical analysis or machine learning techniques to solve (e.g., predictive modeling, data mining, knowledge discovery, statistical correlations, visualizations).
- Requires some level of exploratory analysis.
- Requires some level of data wrangling/munging.
- Can be solved primarily using programming languages like: R, Python, and Java.
- A business or technical contact at the sponsoring organization who can communicate with student teams over the duration of the project.
The capstone project course is typically held in the fall semester, while the practicum course is held in spring. Accordingly, the following deadlines are set for the respective courses:
|Sponsor organization engagement||July 15||December 1|
|Project kick-off meetings||mid-September||mid-Febuary|
Final presentation to sponsor (face-to-face or virtual via Skype)
|early December||early May|