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« Study Bachelor's and Master's in English in Poland
Warsaw, Poland
Kozminski University

Master in Big Data Science

Master's
Table of contents
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⇑Master in Big Data Science at Kozminski University

Language: EnglishStudies in English
Subject area: computer science
Kind of studies: full-time studies
  • Description:

  • pl
Specialities:
University website: www.kozminski.edu.pl/en/

⇑Why study the Master in Big Data Science at Kozminski University?

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Why study it:

The Master in Big Data Science at Kozminski University in Warsaw is a two-year second-cycle (Master's) programme taught in English, run full-time in the evenings, Monday to Friday from 17:00 to 21:00, partly on site and partly online. It suits graduates who want to work with Big Data, AI and machine learning – mainly in finance and health economics – while working at the same time.

Programme: mathematics, statistics and AI from semester one

From the first semester you learn advanced mathematics, statistics and econometrics and apply them straight away in intensive hands-on tutorials and seminars. The programme covers data collection, data analysis, machine learning and AI, and all students also study entrepreneurship, venture capital and cloud computing. Teaching staff include IT and industry professionals, among them people working at Microsoft and Oracle.

Specialisation: Data Analytics or Health Economics

The Data Analytics major develops advanced Big Data and AI skills, mainly for careers in finance but also in other industries.

The Health Economics and Big Data Analytics major applies Big Data, AI and predictive modelling to efficiency, cost management and resource allocation in healthcare, digital health and pharmaceuticals. You work on case studies and real-world data from health systems around the world and meet the programme's partners during workshops.

Labs: cloud platforms and databases

  • programming in R and Python,
  • cloud technologies: Amazon Web Services, Microsoft Azure and Google Cloud Platform,
  • training platforms Amazon AWS Academy, Bloomberg for Education and GitHub for Education,
  • business databases such as Reuters, BankScope, EMIS and Infinancials, and academic ones such as ScienceDirect, ProQuest and JSTOR.

Placements: 130-hour internship

A mandatory 130-hour internship worth 5 ECTS takes place in the fourth semester, or earlier with the Vice Dean's approval – after the first semester.

Qualifications: AWS, Bloomberg and GitHub certifications

During the programme you can prepare for certifications in Amazon AWS Academy (cloud computing), Bloomberg for Education (Bloomberg Market Concepts) and GitHub for Education (AI GitHub Copilot and programming skills), and get support in taking Microsoft or Amazon certification exams. Aspiring founders can use business mentorship and crowdfunding programmes through the Kozminski Business Hub and Venture Capital Fund.

After graduation: finance, tech and healthcare

Graduates work, for example, as:

  • quants, financial analysts and quantitative researchers,
  • machine learning and AI engineers,
  • data scientists and data analysts in the private and public sectors,
  • IT business analysts and consultants,
  • data analysts and data-driven policy analysts in healthcare institutions.

As of the 2026/27 admissions, based on the programme page at kozminski.edu.pl.

⇑Test: Is Master in Big Data Science the right fit for you?

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10 questions · two minutes

1. You’re given a dataset so big your laptop can’t even load it. What do you do?

2. What’s your experience of programming and statistics so far?

3. You spot sudden spikes in some sensor data. How do you handle them?

4. You’ll read research papers, document your code and present your analyses in English, working in an international environment with people from all over the world. How does that sound?

5. A model you’ve built performs brilliantly on the training data but poorly on new data. What do you do?

6. A company wants to analyse millions of mobile app events every day. What interests you most about that?

7. Someone suggests using customer data that was originally collected for a different purpose. How do you react?

8. How do you explain your findings to people with no background in data?

9. Where do you see your career after your Master’s?

10. What motivates you most to pursue a Master’s degree in Master in Big Data Science?

⇑Definitions and quotes

Big Data
Big data is data sets that are so voluminous and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. There are a number of concepts associated with big data: originally there were 3 concepts volume, variety, velocity. Other concepts later attributed with big data are veracity (i.e., how much noise is in the data) and value.
Wikipedia
Data
Data ( DAY-tə, DAT-ə, DAH-tə) is a set of values of qualitative or quantitative variables.
Wikipedia
Data Science
Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.
Wikipedia
Science
Science (from Latin scientia, meaning "knowledge") is a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe.
Wikipedia
Science
Those (natural) laws cannot be circumvented by any amount of piety or cleverness, but they can be understood. Uncovering them should be the highest goal of a civilized society. Not, as we have seen, because scientists have any claim to greater intellect or virtue, but because the scientific method transcends the flaws of individual scientists. Science is the only way we have of separating the truth from ideology, or fraud, or mere foolishness.
Robert L. Park, Voodoo Science (2000), p. 211
Wikiquote
Science
Science has an important part to play in our everyday existence, and there is far too much neglect of science; but its intention is to supplement not to supplant the familiar outlook.
Arthur Eddington, Science and the Unseen World (1929).
Wikiquote
Science
Science is the topography of ignorance.
Oliver Wendell Holmes, Sr., Medical Essays, 211. Quotes reported in Hoyt's New Cyclopedia Of Practical Quotations (1922), p. 691-92.
Wikiquote
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