# Data 1010

### DATA 1010: Probablity, Statistics, and Machine Learning

Course Website [Fall 2021]

Course Description:

In this course we will introduce the mathematical methods of data science through a combination of computational exploration, visualization, and theory. We will learn scientific computing basics, topics in numerical linear algebra, mathematical probability (probability spaces, expectation, conditioning, common distributions, law of large numbers and the central limit theorem), statistics (point estimation, confidence intervals, hypothesis testing, maximum likelihood estimation, density estimation, bootstrapping, and cross-validation), and machine learning (regression, classification, and dimensionality reduction, including neural networks, principal component analysis, unsupervised learning, Bayesian methods, and graphical models).

DATA 1010 is a double-credit, required course for the Sc.M. program in Data Science at Brown University. [Note: starting in AY 22-23, DATA 1010 will no longer be offered. This course will be replaced by a two-course sequence (APMA 1690 or CSCI 1450 and DATA 2060 or CSCI 1420).]