Data Science for Public Policy (MS)

Brooks School of Public Policy

Program Website

Program Description

Recent decades have seen exponential growth in the collection and amassing of data. The explosion of data comes from an ever-growing variety of sources: administrative and institutional operations, internet, video, audio, sensor, and data from businesses. These new data provide new opportunities for making better informed decisions and provide better information to citizens, yet relatively few policymakers and public servants have the appropriate training to do so.

Professional degrees that allow students to learn about data science and gain computing and leadership skills are in high demand, but most of the training in data science is solely focused on technical computing skills and/or on the private sector. Moreover, regulation and policy have been unable to keep up with the fast-paced proliferation of data science tools, like artificial intelligence, and how they are used. Important issues about privacy, ethics, access, and accuracy have yet to be settled. Capably managing these new frontiers of technology will require a workforce that both understands the technical tools and underlying social science and policy analysis frameworks for their use.

Students trained in the Brooks School Master of Science in Data Science for Public Policy (DSP) program will be well-equipped for careers at the local, state, national, and global levels across a range of sectors and industries, both in occupations (like data scientist) focused on utilizing data science tools and in those (like policy analyst) focused on managing or responding to the use of these tools.

Academic Standards

Program Policies

Please review Brooks School Policies and Procedures for detailed information on academic policies and requirements, as well as Cornell University Academic Integrity policies. 

Petitions

Course substitutions may be permitted based on prior mastery of a subject or to request a relevant course not listed within the catalog year’s curriculum requirements. These petitions must be approved by the Data Science for Public Policy Program Director.

Data Science for Public Policy students must be in-residence for all semesters of the program. They must also attend classes according to the modality offered by the course and cannot request an alternative form of attendance/participation.

Students who face an extenuating circumstance may petition the Data Science for Public Policy Director for an exception to a Data Science for Public Policy academic policy.

Academic Standing

Residential master’s students are expected to meet the following academic standards:  

  • Maintain a minimum semester and cumulative grade point average of 3.0.
  • Receive a grade of C or better in all courses applied toward degree requirements.
  • Carry no more than two incomplete grades at any time.
  • Complete at least 12 credits each fall and spring term and 6 credits each summer term, unless an approved petition for a reduced course load has been granted.
  • Remain in residence unless participating in an approved off-campus activity with prior written approval from the program director.  
  • Make satisfactory progress toward completion of a Brooks School master’s degree.

For additional information regarding the academic standing review process, refer to the Brooks School Policies and Procedures.