Data Science for Business

2025/2026

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Finance

Course type:

Elective course

When:

1 year, 2 module

Instructor

Lambert, Jerome

Course Syllabus

Abstract

Today, the amount and type of data is rapidly growing. The modern researcher has a need for flexible and powerful tools for collecting and analyzing information. Python is the industry standard for machine learning and big data analysis. The goal of this course is to develop programming skills and create a solid practical foundation for data analysis and presentation. We will also get acquainted with tasks and different machine learning algorithms, which will set the development vector for those students who want to delve into the subject. In this course, we will refresh our memory of Python programming skills, deepen our skills in working with specialized libraries for data analysis and visualization - numpy, pandas, scipy, matplotlib, plotly. We will solve research problems from setting the problem and collecting data to applying mathematical models to assess the correctness of our hypotheses. To the regression models familiar from statistics, we will add decision trees and a random forest, classification and clustering algorithms to our research tools, and learn how to build social graphs. We will pay special attention to text analysis, because a huge number of research and commercial tasks are tied to it. Also we will discuss what neural networks are and how you can apply ready-made solutions for your tasks.