Advisor and instructor quick guide
The Data Science Labs are one-credit companion courses that help Purdue students turn mathematics into working code, physical measurements, simulations, and data analysis.
Fall 2026 registration: use the current section and CRN table. Share that dated page instead of copying CRNs into email that may be reused in a later semester.
Match a student with a lab
| Lab | Take alongside | Coding preparation | What students build or analyze |
|---|---|---|---|
| MA 16290 | MA 16200 or MA 16600 | No previous programming course required | Sensors, data acquisition, Python foundations, measurement, and error |
| MA 26190 / ECE 29595 | MA 26100 | MA 16290 or prior Python experience | Color, images, video, vectors, and line integrals |
| MA 34990 / ECE 39595 | ECE 301, AAE 301, MA 428, or MA 34900 | Prior Data Science Lab or prior Python experience | Sound, transforms, filtering, and electronic instruments |
| MA 41690 / ECE 39595 | ECE 302, AAE 361, MA 416, STAT 416, or STAT 311 | Prior Data Science Lab or prior Python experience | Simulation, random processes, images, video, and classification |
Useful points to tell students
- Each lab is a focused, one-credit hands-on course connected to mathematics the student is already learning.
- Students use open online textbooks and can preview the materials before registering.
- Eligible students may use a lab to support an honors contract in the paired course; the current syllabus contains the requirements.
- The ECE and MA numbers are cross-listed versions of the same laboratory where shown.
Copy-and-share description
The Data Science Labs are one-credit Purdue laboratory courses that connect calculus, multivariable calculus, signals and systems, and probability to Python, sensors, microprocessors, simulations, and real data. Explore the projects and current sections at thedatasciencelabs.github.io.
Questions
For course fit, honors-contract, or registration questions not answered here, contact Prof. Kaitlyn Hood at kthood@purdue.edu.