Магистратура 2025/2026

Предсказательное моделирование

Статус: Курс по выбору (Бизнес-аналитика и системы больших данных)

Кто читает: Департамент математики

Когда читается: 2-й курс, 1, 2 модуль

Охват аудитории: для всех кампусов НИУ ВШЭ

Преподаватели: Швыдун Сергей Владимирович

Язык: английский

Контактные часы: 48

Course Syllabus

Abstract

Predictive Modeling is a statistical subject taught to the second year graduate students over the first and second academic modules. The material ranges from classical topics such as linear and non-linear regression and classification to less frequently discussed questions such as Markov Chain Monte-Carlo, dynamic linear models, multivariate time series analysis, etc. For each model considered, much attention is paid to performance assessment so as to minimize the forecast error. Throughout the course a certain balance between mathematical rigor and intuition has to be maintained. Often, this dilemma is resolved in favor of illustrative examples which help students capture the main idea and learn how to use it in practice instead of memorizing derivations. Nonetheless, we find it instructive to provide brief and tractable proofs whenever it makes pedagogical or some other sense. Some not too hard theoretical questions are left for home assignments which makes students work with pen and paper and provides a deeper understanding of underlying theory. The practice skills are developed throughout in-class practice sessions and home assignments involving real-life datasets.