MATH 390 Computational Mathematics

This course provides a practical introduction to computational mathematics with a strong emphasis on the development of programming skills for mathematical problem solving. The course introduces essential tools for numerical modeling, data handling, and simulation. Selected numerical analysis topics such as root-finding, Gaussian elimination, interpolation, and error analysis are included. The course also delves into stochastic models, including Markov chains, Poisson processes, and queueing theory, and implementation of Monte Carlo simulations to analyze real-world systems. Throughout the course, students gain experience writing code and interpreting analytical and computational results in business and industry contexts.

Prerequisites

• ICS 140: Computational Thinking with Programming and MATH 320: Probability
• or DATA 211: Data Science and Visualization and IENG 320: Probability and Statistics for Engineering

Special information

Overlap: IENG 390. Note: Formerly known as MATH 420. Students whose prerequisites are not identified by the system should contact the Math and Statistics department for an override at MATH@metrostate.edu.