EC503: Introduction to Learning from Data


Probability, e.g., EC381 or EK500 or EC505, Linear Algebra, e.g., EK102 or MA142, Multivariate Calculus, e.g., MA225, and some level of mathematical maturity. Prior experience with Matlab, e.g., EK 127 is important. Good computer programming skills, e.g., EC327, is desirable.


Provides a strong foundation in probability and an introduction to statistics and machine learning. Includes experience with translating engineering problems into probabilistic models, and working with these models analytically and algorithmically. Prepares students for upper-level electives that use probabilistic reasoning. This course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Critical Thinking.


Yannis Paschalidis


EC503 Syllabus – Spring 2019