18 Credits of Core Courses Required. All Data Science students must take the following Core Courses:
| Credit Hours |
Course No. |
Course Title |
|---|---|---|
| 3 | MAP 5196 | Mathematics for Data Science |
| 3 | COP 5XXX | Introduction to Data Science |
| 3 | STA 5207 | Applied Regression Methods |
| 3 | STA 5635 | Machine Learning |
| 3 | CAP 5771 | Data Mining |
| 2 | PHI 5XXX | Data Ethics |
| 1 | STA 5XXX | Professional Development Seminar |
6 Credits (or more) Scientific Computing Electives Required.
| Credit Hours |
Course No. |
Course Title |
|---|---|---|
| 3 | ISC 5228 | Monte-Carlo Methods |
| 3 | ISC 5307 | Scientific Visualization |
| 3 | ISC 5305 | Scientific Programming |
| 4 | ISC 5315 | Applied Computational Science I |
| 3 | ISC 5318 | High-Performance Computing |
| 3 | ISC 5XXX | Cloud Computing |
| 3 | ISC 5XXX | Probabilistic Programming |
| 3 | ISC 5XXX | Neural Differential Equations |
6 Credits (or more) Free Electives offered by the participating IDS degree programs:
Computer Science
Data Science Electives
Mathematics
Data Science Electives
Scientific Computing
Data Science Electives
Statistics
Data Science Electives
Example course mapping for a three-semester degree:
| Fall Year 1 |
Spring Year 1 |
Fall Year 2 |
|---|---|---|
| [ Core Course ] Mathematics for Data Science (3 credits) MAP 5196 |
[ Core Course ] Machine Learning (3 credits) STA 5635 |
[ Elective ] Scientific Visualization (3 credits) ISC 5307 |
| [ Core Course ] Introduction to Data Science (3 credits) COP 5XXX |
[ Core Course ] Applied Regression Methods (3 credits) STA 5207 |
[ Elective ] Applied Computational Science I (4 credits) ISC 5315 |
| [ Core Course ] Data Mining (3 credits) CAP 5771 |
[ Core Course ] Data Ethics (2 credits) PHI 5XXX |
[ Elective ] Monte Carlo Methods (3 credits) ISC 5228 |
| [ Core Course ] Professional Development (1 credit) STA 5XXX |
[ Elective ] High-Performance Computing (3 credits) ISC 5318 |
|