Course Tasters

Data scientists turn messy real-world numbers into answers someone can act on. You find reliable sources, clean the data, explore patterns with code, then brief a manager on what it shows — and what it does not.

Quants treat markets as data. They measure risk, test trading ideas, compare portfolios under uncertainty, and write research that helps decide what to buy, hold or avoid.

Actuaries put a price on uncertainty. They model how often costly events happen, set fair premiums, estimate pension costs as people live longer, and advise boards on capital and risk.

Machine learning engineers turn tables of measurements into models that predict. They build features, train and evaluate classifiers, watch for overfitting, and report what a model is good enough to decide — and when it is not.

Mapping analysts use computer-vision land-cover maps without building the models themselves. You inspect outputs, spot where a map looks unreliable, and write briefs rangers and ecologists can act on.

Computer vision developers teach machines to interpret images. You turn pixels into arrays, build filters and CNNs in Python, train classifiers on aerial tiles, and evaluate where the model succeeds or fails.