The Senior Capstone Project offers the opportunity for organizations to propose a project that our graduate students will work on as part of their curriculum for one semester. Below you will find information on the course along with a questionnaire to propose a project. If you prefer to answer via a word document, please download the document here: CDS-Senior-Capstone-Project-Proposal, include your answers within the document and send as an attachment to Andres Borray ab4829@nyu.edu

CDS Project Proposal Template

Students, fellows and research engineers at NYU CDS are actively engaged in research. At any given time, a large number of highly skilled data scientists-in-training are looking for new research opportunities and external projects. In particular, all master’s students (and many CDS faculty) participate in the Master’s Capstone at CDS, carried out in the final year of the NYU CDS Masters in Data Science program. These projects involve groups of roughly 2-4 students working in partnership with outside organizations that have provided real problems that can be solved via applications of data science. The outcome is a win-win: the students get the opportunity to work in their field of interest and gain exposure, while the partners receive the benefit of having a new perspective applied to their projects.

The NYU CDS community includes individuals from many different industries and disciplines; therefore, we will be searching for a number of data science projects/problems that our students can tackle. We hope to gather a diverse set of problems that address the different subject matter and technical requirements.  We ask that all academic and industry partners help us to specify projects using the template below. Responses to each of the questions will allow us to identify the right people within the CDS student and faculty community to carry out, mentor, and evaluate each project and tackle your problems.  Answers to each point below are required but can be very brief; a few sentence answers to each point below are all that is required in most cases.

CDS our students are trained to apply data science to the following fields. It may help you identify projects or solutions to problems you are seeking to address:

 

  • Probability and statistical analyses.
  • Natural language processing.
  • Big Data analysis and modeling.
  • Machine learning and computational statistics.
  • Coding and software engineering.
  • Visualization modeling.
  • Neural networks.
  • Signal processing.
  • High dimensional statistics.

 

  • The projects that organizations provide to our students need to be engaging, relevant, and of a scope that can be accomplished within the capstone-course timeline. Please refer to the list of applications above, to identify and describe the question or problem you are seeking to use data science to address.
  • Please provide a detailed description of the type of data required to address the problem identified in the previous question. For example, will the students primarily be working with data aggregated from twitter feeds or other social networks, or is it medical data, biological data, or financial data? Please also provide context regarding where the data can be found. Will the organization provide the majority of the data? Is the data accessible publicly or via other avenues/sources? Is a non-disclosure agreement (NDA) required? How much of the data is currently available? Do the students need to gather data, model data, both, or neither?
  • Please estimate the number of people needed, for example, is this a project that 1, 2 or 4 people can address? How many hours of work are anticipated for completion of the project? Is this a smaller well-delimited problem or the next step in addressing a larger challenge in your field?
  • The Center for Data Science must grade all of the final projects for the students to receive course-credit. Therefore, each problem must be accompanied by a detailed description of the rubrics of success. To do this, we need information from the stakeholders about what progress/success would look like. For example, is progress classified as the creation of an algorithm that improves upon the current process? What are the quantitative and qualitative metrics that can be used as metrics for successful completion of the capstone project? Since each problem would ideally propose a different set of solutions, these rubrics must be specific to each individual problem.
  • Please provide information on the relevant background information that someone working on the project should have. You can provide this in any format most convenient and expedient, such as: citations, outside links or text.
  • Please provide a brief description of the company or organization’s history and what it is it does more broadly. This context will allow us to match students with outside organizations that are relevant to their specific long term interests.
  • One of the most beneficial aspects of this capstone course project is the opportunity for students to work with professionals in different industries. Each organization must commit to providing mentorship to the students so that they can receive real-time feedback and guidance from the organization they are working with. While some of the support will come from CDS including one outreach program manager and an academic fellow, we want everyone proposing a project to specify who is the person in the organization that will work with the students to guide and evaluate the project. Ideally this organizational-contact would also be available to assist in the review process once the project is completed to help our faculty asses the metrics of success. Please state who will work with the student or CDS project team? What are their qualifications or training? What amount of time per week do they intend to devote to working with the project team?
  • We ask that you also provide feedback on this template and the Senior Capstone project so that CDS can improve this course every year. Please feel free to provide feedback here or feel free to send to Andres Borray at ab4829@nyu.edu.