Step 1 - Choose a Problem to Solve
A brief statement about the problem that the project tackles. The projects need to be focused on a data science problem that is engaging, relevant, clearly defined and of the right scope for a semester. When assessing the proposals, we will be looking for a diverse set of problems that address different topics and technical requirements that our students can address.
Step 2 - Identify datasets that can be used to address the problem statement.
Potential datasets that you can be made available to the student team. These can be public datasets or proprietary datasets. If the latter, we can discuss NDAs and proper practices to protect the data. Additional datasets can be identified in the course of the project but there should be a solid grounding in some core datasets at the outset.
Step 3 - Envision the outcome
Defining what is expected from the team to deliver - an algorithm, a dashboard, a visualization, etc.
Step 4 - Identify team members who will work with the QMSS team
There should be at least one, but ideally, three or four team members who are working with the QMSS team to specify project parameters, provide feedback, and answer data or other questions from the student team. Ideally, these will be people very familiar with the datasets and/or the problem to be addressed. Step 5 - Specify communication frequency We have found that usually a meeting every two weeks works well but it really depends on the project.
If you are interested in submitting an initial proposal, please use this form to start a conversation with us. Potential Partnership Proposal
