This course introduces the essential mathematical concepts and computational techniques that form the basis of modern computing. The course emphasizes problem-solving, mathematical reasoning, and connections between mathematics and computing, preparing students for advanced study in theoretical and applied areas. This course is required for all concentrations in the Mathematics and Computing major.
Math 1499 is a one-credit studio course that may be taken in conjunction with Math 1551 (Differential Calculus) by students who need extra support in the Precalculus topics used in Calculus.
All students in Math 1499 should enroll concurrently in Math 1551.
Some students are required to enroll in Math 1499 based on their Math placement scores, but any student wishing for additional support is welcome to enroll.
This 3-credit hour course introduces essential concepts in probability and statistics for students in the Mathematics and Computing undergraduate major.The course focuses on and works toward concepts in probability and statistics that are important for problems in computing and machine learning, such as statistical inference, in particular parameter estimation, and sampling/simulation methods such as Monte Carlo methods. This is in contrast to topics in hypothesis testing and confidence intervals that may be more important to students in t
The following table contains a list of all undergraduate special topics courses offered by the School of Math within the last 5 years. More information on courses offered in the current/upcoming semester follows below.
The following table contains a list of all graduate special topics courses offered by the School of Math within the last 5 years. More information on courses offered in the current/upcoming semester follows below.
A comprehensive overview of advanced material in analysis. This is a Mother Course with 5 different subtitles; Recommended prerequisites may vary with each offering.
This course is an introduction to theoretical statistics for students with a background in probability. A mathematical formalism for inference on experimental data will be developed.
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, MATH 3670, and MATH 3740 are mutually exclusive; students may not hold credit for more than one of these courses.
