Interdisciplinary Data Science - Master [2 Years]
$65,684 /Yr On-campus full_time

Master of Science [M.S] Data Science

  • Master in Interdisciplinary Data Science is a two-year program at Duke University.
  • It is an on-campus program offered on a full-time basis.
  • Students will work with Duke’s elite faculty in fields across the university including computer science, statistics, math, economics, political science, sociology, medicine, neuroscience, law, and history.
  • Master in Interdisciplinary Data Science program is structured to connect technical learning and expertise with the many domains in need of data insights.
  • MIDS combines rigorous computational and technical training with field knowledge and repeated practice in critical thinking, teamwork, communication, and collaborative leadership to generate data scientists who can add value to any field.
  • The enrollment of the students in this program is 35 – 40.

Tution & Application Fees

Year Year 1 Year 2
Tuition Fees $60220 $60220
Health Insurance $3375 $3375
Books and supply $668 $668
Other Fees $1421 $1421
Total Fees $65684 $65684

Examinations

Exam Type Exam Name Score Out of Score Exam Level
IELTS International English Language Testing System 7.0 9 3
TOEFL Test of English as a Foreign Language 90 120 3
GRE Graduate Record Examination 315 340 2

Academic Eligibility: 

  • Students must have a  bachelor's degree from an accredited institution.
  • Students required an average grade of 3.0 on a 4.0 scale.

Indian Student Eligibility:

Indian students are eligible to apply if they meet one of the following eligibility criteria:

  • Students must complete a 4-year undergraduate degree from a recognized institution
  • Or, students completed a master's degree with first-class in a relevant field from a recognized institution.

Along with the minimum eligibility requirements, international students hailing from non-English speaking countries need to prove English proficiency through IELTS/TOEFL/any equivalent test to get admission to this program.