NEW Course Offered in Spring 2021! CSE 40: Machine Learning Basics: Data Analysis and Empirical Methods

Description:   This course provides an introduction to the basic mathematical concepts and programming abstractions required for modern machine learning, data science and empirical science.   The mathematical foundations include basic probability, linear algebra and optimization.   The programming abstractions include data manipulation and visualization.  The principles of empirical analysis, evaluation, critique and reproducibility will be emphasized.   Mathematical and programming abstractions will be grounded in empirical studies including data-driven evidential reasoning, predictive modeling and causal analysis.


This course is a great first introduction to machine learning and an ideal preparation for upper division ML and AI classes.


The prerequisites to CSE 40 are: Math 19B or Math 20B, and CSE 30.