IS 4520 Software Project Management 3.0 Credits
Develops the computational and quantitative techniques needed to develop and implement analytic methods, including model training, statistical inference, approximation, and estimation. Building on foundational calculus and computational skills, this class introduces more complex analytic techniques and explores their quantitative foundations. Demonstrates advanced toolkits in numerical computing and introduces techniques for statistical inference and model optimization used in learning applications. Presents foundational knowledge on the definition and function of analytic processes that underlie prediction, measurement, and optimization. Course provides experience understanding numerical representation effects and introduces parameterization in relation to inference and data analysis.
Repeat Status: Not repeatable for credit
Prerequisites: IS 2500 [Min Grade: D] or CS 1020 [Min Grade: D] or CS 1030 [Min Grade: D] or INFO 200 [Min Grade: D] or CS 171 [Min Grade: D]