Fall 2026 · 1 credit
MA 34990 / ECE 39595: The Data Science Labs on Signals and Systems
An accessible HTML adaptation of the Spring 2026 syllabus, updated for the verified Fall 2026 cross-listed offering.
Course information
| Sections | CRNs | Meeting time | Location | Teaching assistant |
|---|---|---|---|---|
| MA 34990-002 / ECE 39595-010 | 27360 / 29064 | Wednesday, 6:00–8:50 PM | Brown Hall 215 | To be announced |
Coordinator
- Name: Prof. Kaitlyn Hood
- Email: kthood@purdue.edu
- Office hours: To be announced
- Role: course administration, course structure, and honors contracts
Course description
This one-credit course consists of weekly face-to-face computer laboratories. Projects apply Fourier analysis and signals-and-systems ideas to data science while providing practice with Python, sensors, and microprocessors.
- Prerequisite: MA 16290, MA 26190, or prior Python programming experience.
- Corequisite: ECE 301, AAE 301, MA 428, or MA 34900.
Textbook and calendar
The Data Science Labs on Fourier Analysis, Jupyter notebooks by M. Boutin and A. Bradford.
Learning objectives
By the end of the course, students will be able to:
- Write Python code to collect and analyze data from sensors and microprocessors.
- Use sinusoidal functions and transformations to play sound.
- Use the I2S protocol to build a synthesizer and a theremin.
- Use the laws of sines and cosines to describe beats and build a voice changer.
- Implement and use the discrete Fourier transform to analyze and denoise signals.
- Build a pedometer and use frequency analysis to tune an instrument.
Grading and assignments
A Jupyter notebook report is created for each laboratory and submitted by the Gradescope deadline. The course grade is based on the laboratory reports. A graded lab may be corrected and resubmitted for full credit at most twice; students may submit no more than one regrade request per week. The lowest lab grade is dropped.
| Letter | Percentage | Letter | Percentage |
|---|---|---|---|
| A+ | 97% or higher | C+ | 77–79.9% |
| A | 93–96.9% | C | 73–76.9% |
| A− | 90–92.9% | C− | 70–72.9% |
| B+ | 87–89.9% | D+ | 67–69.9% |
| B | 83–86.9% | D | 63–66.9% |
| B− | 80–82.9% | D− / F | D−: 60–62.9%; F: below 60% |
Attendance
Attendance is mandatory unless the teaching assistant explicitly excuses an absence.
- First-two-week absences are automatically excused but require one announced make-up session per missed lab.
- Later requests should be submitted promptly with documentation; make-ups require explicit approval.
- For an exam conflict, contact the exam administrator early. Scheduled classes take precedence under Purdue policy.
- Arrive on time. Late arrival may result in a report penalty. Students may leave after submitting the required work.
Academic integrity, artificial intelligence, and equipment
Students may discuss approaches, but submitted reports and code must be their own work. Do not share final code or solutions or post them publicly. Academic-integrity incidents may result in a failing course grade and referral to the Office of the Dean of Students.
Writing and understanding Python is a central objective. Unless a use is explicitly authorized, submitted work must not be produced by AI or a large language model and must reflect the student's own understanding.
Handle sensors, microprocessors, and other laboratory equipment carefully. Intentional theft or damage is treated as an academic and conduct matter.
Honors contracts
MA 34990 may be used to earn honors credit for ECE 301, AAE 301, or MA 34900. A student must take the paired course during the same semester, submit the contract by the second Friday, and earn a passing grade in MA 34990. College of Science and College of Engineering contracting procedures differ; consult Prof. Hood and Brightspace.
Laboratory sequence
- Introduction.
- Playing sound.
- Build a synthesizer.
- Build a theremin.
- The human experience of sound.
- Tremolo and beats effects.
- Build a voice changer.
- Chirps, bells, and other instruments.
- The discrete Fourier transform.
- Frequency analysis with the DFT.
- Build a pedometer.
- Tune an instrument.
The dated public calendar and Brightspace/Gradescope entries determine exact dates.
Hardware
Raspberry Pi Pico, accelerometer, ultrasonic distance sensor, and associated audio components.
Accessibility
Purdue strives to make learning experiences accessible. Students who anticipate or experience disability-related barriers should contact the Disability Resource Center at drc@purdue.edu or 765-494-1247. If accommodations are approved, send the Course Accommodation Letter to the teaching assistant and discuss implementation promptly. Read the Course Accommodation Letter instructions.
Emergency and university information
In a major campus emergency, requirements, deadlines, and grading details may change. Updates will be sent through Purdue email and Brightspace. Brightspace provides the current accessibility, nondiscrimination, mental-health, and basic-needs links.
Public syllabus URL: https://thedatasciencelabs.github.io/syllabi/ma34990-fall-2026.html