A career-boosting
data science bootcamp

Bratislava — 4-8 March 2024



PhD students who need to handle data, use statistics or build models in their research.


Analysts who want to swing away from Excel and start working with big data, applying machine learning and create eloquent visualisations.


Professionals wanting to learn more about machine learning and statistics.


  • Intense 5-days of coding and thinking about data science problems
  • Hands-on workshops with real-world datasets and data challenges
  • Interactive lectures on important data science concepts
  • Group projects with individual support by our expert team
  • A combination of theoretical and practical workshops
  • A data-hackathon on the 5th day


  • Educate about data science
  • Provide the necessary skills to handle data
  • Raise awareness of strengths and weaknesses of machine learning models
  • Cover the important topics often overlooked by online courses
  • Advance the research and performance of the attendees by supporting their journey towards data literacy
  • Talk about problems that seniors encountered in their workflows
  • Teach how to avoid "junior" mistakes in interpretation of analytical results


  • Welcome and Opening. Intro to python and data processing (day 1)
  • Data Visualisation (day 2)
  • Statistics and regression modelling (day 3)
  • Machine Learning (day 4)
  • Data-hackathon (day 5)
    • 3 data challenges to choose from
    • Aim: solidify concepts and skills acquired during first 4 days in practical challenges


  • Welcome and opening
  • Presentation: Data Science
  • Intro to Python programming
  • Strings handling
  • Data importing, cleaning, filtering in Pandas library
  • Data storage
  • Missing values and data aggregation
  • Data visualisation
  • Interactive graphs
  • Dashboards
  • Geographical plotting
  • Presentation: Data communication
  • Multivariate plots
  • Intro to Statistical Inference and Hypothesis testing
  • Presentation: Causality vs Correlation
  • Regression Modelling
  • Presentation: Predictive performance measures
  • Logistic Regression
  • Presentation: Statistics vs Machine Learning
  • Exercise: Exploratory data analysis
  • Intro to Machine Learning
  • Supervised Learning (Prediction)
  • Model inspection, feature importance, partial dependence
  • Unsupervised Learning (Clustering)
  • Dimensionality Reduction, Anomaly detection
  • Presentation: Interpretability vs complexity
  • Looking for the best predictive performance
  • Mini-hackathon
  • Group projects
  • Real world problems


  • Start - 4 Mar 2024
  • End - 8 Mar 2024
  • A course day starts at 9:00 and ends at 18:00 with breaks for coffee and lunch.
  • No programming experience is required to attend (however, we highly encourage checking out the recommended topics to familiarise yourself with before the bootcamp).
  • We will emphasize data visualization and writing simple clean code during the course.
  • Participants will encounter plenty of data cleaning problems along the exercises.
  • Forums for knowledge and experience exchange are an essential aspect of the bootcamp.

Required knowledge

Basic quantitative skills
No programming skills needed

Familiarity with computer programming or database structures is a benefit, but not a requirement. Winter Data School is set up in a way that beginners will learn the basics and do some hands-on experimentation with guidance, while participants with some experience will be able to see best practices, utilise their knowledge and do some additional magic on really cool datasets while consulting with experienced mentors!


Widely considered as one of the best programming languages for beginners, Python is a general purpose language that is currently the best choice for data science and machine learning applications. During the first day, we will walk you through the basics of this language and how to use it to solve data science tasks.


By attending Winter Data School, you will gain lifelong access to our data science community. We support our members online, and in person by organizing monthly events such as discussions, short lectures and workshops, and data challenge evenings. The participants of our previous event, Winter Data School, found work opportunities and research collaborations in this community. As community is one of our core values, we listen closely to your feedback and try to accommodate what the members want in our events. Join this wonderful community and gain access to a unique resource for learning data science!


Price - 1000 EUR


Price - 900 EUR


Price - 800 EUR

Thanks to our partners, we are able to provide 10 scholarships to students (undergraguate, masters and PhD). This scholarship covers 100% of the costs of Winter Data School. If you are a student and wish to apply for the scholarship, please fill out the sign-up form accordingly and write a short (500 words maximum) motivation statement - the scholarship will be awarded based on this statement.

Our scholarships are intended to support those who (or their research groups in the case of PhDs) cannot otherwise afford the entry to Winter Data School. It is worth noting that the acceptance rate to this scholarship was 30% on our previous event, Winter Data School 2023. If a participant applies and is not granted the scholarship, they will be offered to buy the entry, however this is subject to availability of places, which may be exhausted.

  • 5 days of lectures and workshops by industry leaders
  • Exercises and mentoring
  • Carefully prepared curriculum
  • Presentations from external speakers
  • Networking opportunities
  • Knowledge exchange
  • Membership in the new data science community with monthly events


Imrich Berta

Applied mathematics graduate from University of Cambridge, experienced in machine learning models for disease prediction. Currently works as a consultant for government on cancer epidemiology and public health. Actively mentors analysts and organizes coding workshops for students.

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Laura Johanesová

Laura is a bioinformatician and biomedical scientist currently at the University of Vienna. The skills she has in R, Linux and Python are crucial for her research in regeneration and she also developed interest in biotechnology and medicine, which helped her team win the first place in a biotech incubator.

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Jakub Hantabal

Jakub is a biomedical data scientist studying at Oxford and specializing in oncology collaborating with British and Slovak institutions. Jakub also consults clients in life science on business and technology development, and is passionate about education of future data scientists.

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Ján Dudek

Magna cum laude economics and econometrics graduate from Rice and Oxford. Improved the risk-equalization model at the Ministry of Health and implemented ML fraud detection algorithms in Slovak healthcare. Currently a senior data scientist specializing in the health insurance industry.

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