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Cross-listed one-credit laboratory

MA 41690 / ECE 39595: Probability

Projects connect introductory probability to simulation, sensor data, images, video, and classification.

Prerequisite: Prior Data Science Lab or prior Python experience
Corequisite: ECE 302, AAE 361, MA 416, STAT 416, or STAT 311
Format: Weekly face-to-face computer laboratory

Monte Carlo simulation with random points inside and outside a circle used to estimate pi — Students estimate pi by simulation and use repeated random experiments to study error, variance, and convergence.

What students do

Interpret probability as frequency and work with conditional probability.
Quantize images and detect motion in video.
Create and evaluate random-number generators.
Estimate pi with Monte Carlo methods and classify data with naive Bayes.

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