FSU’s Interdisciplinary Data Science Master’s Degree Program curriculum is delivered exclusively at the university’s Tallahassee campus. Students will complete a series of core courses that provide a solid starting point in mathematics, machine learning, statistics, data ethics, and data science, along with electives that support a specific major area of study.
All students take 18 credits of core coursework and 12 credits of elective courses, selected by the student together with their advisory committee, to define a specific major — computational science, computer science, mathematics or statistics.
Interdisciplinary Data Science Core Coursework
 MAP 5196  Mathematics for Data Science (3)
 CAP 5768  Introduction to Data Science (3)
 STA 5207  Applied Regression Methods (3)
 STA 5635  Machine Learning (3)
 CAP 5771  Data Mining (3)
 PHI 5699  Data Ethics (2)
 STA 5910  Professional Development Seminar (1)
The remaining 12 credits are elective courses, which effectively define the different majors. Elective choices are listed for each major.
Interdisciplinary Data Science: Computational Science
Required Electives:
 None
Restricted Electives (Choose two or more courses from the following):
 ISC 5228  MonteCarlo Methods (3)
 ISC 5307  Scientific Visualization (3)
 ISC 5305  Scientific Programming (3)
 ISC 5315  Applied Computational Science I (4)
 ISC 5318  HighPerformance Computing (3)
 ISC 5308 – Data Assimilation (3)
 ISC 5935  Computational Probabilistic Modeling (3)
 ISC 5935  Data Science for Health (3)
 ISC 5935 – AI Methods and Application (3)
Free Electives:

Two courses from among the electives offered by the other majors participating in the IDS program.
Interdisciplinary Data Science: Computer Science
Required Electives (Choose two courses from the following):
 CAP 5769  Advanced Topics in Data Science (3)
 CAP 5778  Advanced Data Mining (3)
 CAP 5XXX – Projects in Data Science (3)
Restricted Electives:
One course in Cybersecurity chosen from the following, based on student background:
 CIS 5379  Computer Security Fundamentals for Data Science (3)
 CIS 5370  Computer Security (3)
One course from the following:
 CAP 5619  Deep and Reinforcement Learning (3)
 CAP 5605  Artificial Intelligence (3)
 CDA 5125  Parallel and Distributed Systems (3)
 CDA 5155  Computer Architectures (3)
 CNT 5505  Data and Computer Communications (3)
 CNT 5605  Computer and Network Administration (3)
 COP 5570  Concurrent, Parallel, and Distributed Programming (3)
 COP 5611  Advanced Operating Systems (3)
 COP 5725  Database Systems (3)
 COT 5405  Advanced Algorithms (3)
 ISC 5318  High Performance Computing (3)
Interdisciplinary Data Science: Mathematics
Required Electives:
 None
Restricted Electives (Choose at least three courses from the following):
 MAD 5XXX  Principles and Foundations of Machine Learning (3)
 MAD 5XXX  Numerical Linear Algebra (3)
 MAD 5420  Numerical Optimization (3)
 MAD 5306  Graphs and Networks (3)
 MTG 5356  Topological Data Analysis (3)
 MAP 5345 – Partial Differential Equations (3)
Free Electives:
 CAP 5769  Advanced Topics in Data Science (3)
 STA 5326  Distribution Theory and Inference (3)
 STA 5166  Statistics in Application I (3)
 STA 5167  Statistics in Application II (3)
 MAD 5403  Foundations of Computational Mathematics (3)
 MAD 5404  Foundations of Computational Mathematics II (3)
 MAP 5345  Partial Differential Equations (3)
Interdisciplinary Data Science: Statistics
Required Electives:
 None
Restricted Electives (Choose three courses from the following):
 STA 5066  Data Management and Analysis with SAS I (3)
 STA 5067  Advanced Data Management and Analysis with SAS (3)
 STA 5106  Computational Methods in Statistics I (3)
 STA 5107  Computational Methods in Statistics II (3)
 STA 5166  Statistics in Applications I (3)
 STA 5238  Applied Logistic Regression (3)
 STA 5326  Distribution Theory and Inference (3)
 STA 5327 – Statistical Inference (3)
 STA 5507  Applied Nonparametric Statistics (3)
 STA 5707  Applied Multivariate Analysis (3)
 STA 5856  Time Series and Forecasting Methods (3)
 STA 5939  Introduction to Statistical Consulting (3)
 STA 6557  Object Data Analysis (3)
Free Electives (Choose one course from the following):
 ISC 5305 – Scientific Programming (3)
 ISC 5307  Scientific Visualization (3)
 ISC 5318  High Performance Computing (3)
 CAP 5605  Artificial Intelligence (3)
 MAD 5306  Graphs and Networks (3)
Internship Course
IDS 5945* – Students must enroll in this course in order to get credit for internships. This is a zerocredit course that provides for proof of internship on the transcript.
*Graduate Zero SemesterHour Courses and Fees
Students registered for zero semester hour graduate level courses and additional courses will not be charged for the zerocredit hour course. When registering for a zerocredit hour course only, the student will be charged for one semester hour at the Florida Resident tuitionrate of the course level. Zero credit courses do not count toward the 12 hours of elective credit, but will be reflected on the final transcript.