University of Technology
Technological sciences
Bachelor Programme
Mode of studies: 
full-time programme
3,5 years
Tuition fee: 
8000 PLN per academic semester
Degree awarded: 
Bachelor of Science
Scholarships available: 
After 1st year best students can apply for Rector's scholarship
Application deadline: 
Wednesday, 10 July, 2024
Day of semester start: 
Tuesday, 1 October, 2024
Credits (ECTS): 
210 ECTS
Admission requirements: 

On our website - www.rekrutacja.p.lodz.pl under " International Candidates" you can find information concerning the admission process including: the list of required documents, available courses, grades required for entry, tuition fees, scholarships, contest- study for free, language requirements etc.

You can also use our search engine to check the programmes offered at TUL and choose the most suitable ones - https://rekrutacja.p.lodz.pl/en/study-programmes?jezyk[]=307&jezyk[]=308


Thanks to the studies in MATHEMATICAL METHODS IN DATA ANALYSIS, you will discover knowledge that will allow you to explore data and make the right decisions based on it. Statistical data analysis will have no secrets for you, you will master the issues of classification, and you will learn to use stochastic methods in forecasting. The structure of the study program allows you to acquire not only mathematical knowledge that will enable you to build and evaluate data analysis models. You will also gain IT skills allowing for its practical use. In addition, by studying in English and gaining soft skills, in particular related to teamwork, you will be able to easily work in international companies. As a graduate of Mathematical Methods in Data Analysis, you can work wherever there is a need for database management, e.g. in the banking sector, in the insurance sector, in the medical market. Consultations of the study program with companies have shown that a graduate with such competences is very much in demand on the labour market.

the ability to use basic methods and algorithms of data mining in current programming environments (R, Python, VBA),
knowledge of algorithms and computational methods important in data mining, including algorithmic methods of linear algebra, machine learning (R) methods, Big Data,
ability to use information systems in extracting knowledge from data (R, SQL, Python),
experience in designing innovative business data analysis applications (Power BI, Python).

Cooperation with companies: 

ING Tech,
Pekao SA.

Job perspectives: 

A graduate of the field of study may work in the following professions:

data analyst,
market analyst,
database designer and developer.

A graduate may also undertake second-cycle studies in mathematics, statistics, IT or in the field of data analysis, both in Poland and abroad.