DS DS 122 is the third in a three-course sequence (with CDSDS 120 and CDSDS 121) that introduces students to theoretical foundations of Data Science. DS 122 covers topics in probability (including common probability distributions, conditional probability, independence, Bayes Theorem, prior and posterior distributions, sampling, and the central limit theorem), statistics (including maximum likelihood), basic numerical optimization (including gradient descent methods), and topics in calculus (including sequences and series). Knowledge of a programming language (such as Python) is expected. Effective Spring 2022, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Critical Thinking.

Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.