Archived:

## Mathematical Foundations of Data Science

Modern data science methods and the mathematical foundations: linear regression, classification and clustering, kernel methods, regression trees and ensemble methods, dimension reduction.

## College Algebra

Study of the properties of algebraic, exponential, and logarithmic functions as needed for pre-calculus and calculus.

## Probability Theory

This course is a mathematical introduction to probability theory, covering random variables, moments, multivariate distributions, law of large numbers, central limit theorem, and large deviations.

MATH 3215, MATH 3235, and MATH 3670 are mutually exclusive; students may not hold credit for more than one of these courses.

## Mathematical Problem Solving

Pass/Fail basis. This course is intended to teach general mathematical problem solving skills, and to prepare students to take the Putnam Examination.

Pass/fail basis.

This course provides students with a broad exposure to areas of mathematics research through weekly speakers.

## Probability and Statistics with Applications

Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression and analysis of variance.

MATH 3215, MATH 3235, and MATH 3670 are mutually exclusive; students may not hold credit for more than one of these courses.

## A Second Course on Linear Algebra

This course will cover important topics in linear algebra not usually discussed in a first-semester course, featuring a mixture of theory and applications.

## Introduction to Discrete Mathematics

Mathematical logic and proof, mathematical induction, counting methods, recurrence relations, algorithms and complexity, graph theory and graph algorithms.

## Foundations of Mathematical Proof

An introduction to proofs in advanced mathematics, intended as a transition to upper division courses including MATH 4107, 4150 and 4317. Fundamentals of mathematical abstraction including sets, logic, equivalence relations, and functions. Thorough development of the basic proof techniques: direct, contrapositive, existence, contradiction, and induction. Introduction to proofs in analysis and algebra.

## Quantum Information and Quantum Computing

Introduction to quantum computing and quantum information theory, formalism of quantum mechanics, quantum gates, algorithms, measurements, coding, and information. Physical realizations and experiments. Crosslisted with PHYS 4782