Bachelor 2024/2025

Research Seminar "Data Analysis in Finance"

Type: Elective course (Software Engineering)

Area of studies: Software Engineering

Delivered by: Big Data and Information Retrieval School

Where: Faculty of Computer Science

When: 4 year, 1-3 module

Mode of studies: offline

Open to: students of one campus

Instructors: Степанченко Дмитрий Сергеевич

Language: English

ECTS credits: 3

Contact hours: 48

Course Syllabus

Abstract

The specialization seminar offers the opportunity to study subjects and sections of mathematical statistics related to the application of differential equations, machine learning, probability theory and mathematical for modeling various solutions of a wide range of theoretical and applied problems. These tasks include analysis and forecasting of time series, automatic detection of trend changes, forecasting “black swan” events, and analysis of stable configurations in the community. The computational methods used are standard for machine learning: clustering, pattern recognition, dimension reduction. The purpose of the research seminar is to expand the research horizons of students. It is assumed that at the end of the course, the student will be able to prepare a research paper or grant application. To do this, the student will be involved in the following activities: attending classes (it is obligatory), analyzing a large number of sources in a foreign area for the student in order to learn how to highlight mathematical problems in non-mathematical articles, completing part of a group project, preparing presentations and discussion (peer review) of other people's projects and presentations. Prerequisites Knowledge of basic mathematics: analysis, linear algebra, probability theory, - algorithms, programming fundamentals, the ability to understand computational packages