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The Winter School in Data Literacy is a module of Certificate in Data Literacy, which aims to provide participants with the skills necessary to transform data into knowledge.

Participants of the Winter School in Data Literacy will be put into groups of 3 to 4 persons made up of participants from various ENHANCE universities.

Participants will be given an open project challenge in Data Literacy scope that will be reviewed by academic teachers from Warsaw University of Technology, Technical University of Berlin and Valencia Polytechnic University.

Winter School is FREE OF CHARGE.
The Blended Intensive Programme (Erasmus+) will
support students' participation.


  • Completed at least the first year of bachelor studies
  • Basic Mathematics such as: function, matrices, basic graph theory e.g. definition of tress
  • Statistics and Probability
  • Programming: nice to have but not necessarily
  • Well-developed social competences


The Winter School activity will be held in hybrid mode. On site in Warsaw University of Technology and then continue in online mode via MS Teams


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The Winter School in Data Literacy schedule is split into two sections:

Training Section

On this section, participants will be equipped with necessary knowledge delivered by tutors; training modules will be provided. Students will learn: Introduction to Python (focused on data analysis), machine learning, and text processing.

Project Section

In accordance with the assumptions of the Problem Based Learning methodology, at the very beginning of the Winter School, students will be provided with a challenge. The challenge will be solved up to the end of the Winter School, gaining the necessary knowledge. 



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Guided tour of laboratories at the Centre for Advanced Materials and Technologies CEZAMAT on 6 February 2023 which consists of:
⦁ Intelligent Semiconductor Systems Department (SEMINSYS) CEZAMAT presentation
⦁ SEMINSYS lab tour

Informal dinner on Wednesday, 8 February 2023 at 17:30.


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José V. Benlloch-Dualde earned a MSc. in Physics from the Universitat de València, and a Ph.D. in Computer Engineering from the Universitat Politècnica de València (UPV). He is currently Senior Lecturer with tenure at the School of Informatics in the UPV, where he teaches different courses related to Electronics and Educational Technology. His research interests relate to technology-enhanced learning and, more in particular, to learning analytics. He has leaded different innovative projects for over twenty years with a specific focus on technology-enhanced learning. He earned a Hewlett- Packard Technology for Teaching Grant Initiative, Transforming Teaching and Learning through Technology in 2008. He was also one of the recipients of the Excellence in Teaching Award from UPV in 2009. He is currently the Teaching Deputy Head of the Computer Engineering Department at the UPV.

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F. Buendía-García obtained his MSc and PhD in Computer Engineering from the Universitat Politècnica de València (UPV), Spain in 1992 and 2003, respectively. Currently, he is an associate professor with tenure at the UPV, where he teaches courses on Computer Engineering. His research interests are related to web technologies and healthcare e-learning.  

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Anna Cena obtained her Ph.D. in Computer Science from Systems Research Institute Polish Academy of Sciences in 2018. Her research interests include machine learning algorithms - with a particular focus on clustering algorithms, mathematical and applied statistics, and data aggregation and fusion methods. Currently, Anna Cena is an Assistant Professor at Faculty of Mathematics and Information Science Warsaw University of Technology where she teaches various classes on data processing, exploration and visualization as well as introductory and advanced courses on R and Python programming languages. Moreover, she acts as a Dean's Proxy for Data Science Studies and is a member of the Program Committee for the Data Science program. 

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Anastasiya Danilenka received her Master's degree at the Warsaw University Of Technology and is now continuing her research as a PhD student at the Faculty of Mathematics and Information Science. Her research interest lies in the field of Federated Learning and its application to Computer Vision problems. She is a skilled data scientist with more than 6 years of both commercial and R&D experience.

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He is a PhD student in Warsaw University of Technology, his research interest is focusing on implementation of artificial intelligence tools in the area of the healthcare sector. He have been a part of a tertiary care hospital for nine years and that's when he developed an interest to transform healthcare through AI technology. He has mission to immerse himself in scientific research and help improve the practical ways. He committed to achieve excellence through enhancement of his own skills, creative thinking and delivering a significant contribution to society.

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Soveatin Kuntur was an awardee of Ignacy Łukasiewicz Scholarship Programme to pursue her master degree in Polish public university. She obtained her master’s degree from Warsaw University of Technology and now she is a freshman PhD Studies in Warsaw University of Technology. Her research interest includes Natural Language Processing and its implementation to real-life problem. Professionally, she is experienced Software Tester and Data Analyst. 

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Timm Teubner is professor of Trust in Digital Services at TU Berlin and Einstein Center Digital Future (ECDF). From 2004 to 2010, Teubner studied Industrial Engineering & Management at Karlsruhe Institute of Technology (KIT), where he also completed his doctorate and worked as a postdoctoral researcher. He spent one year studying at the University of Massachusetts (UMass), Amherst, US. His research takes the perspectives of information systems and economics and focuses on topics such as online platforms and multi-sided markets, reputation systems, trust in digital services, Internet user behavior and psychology, as well as crowdsourcing.

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Anna Wróblewska is an assistant professor at the Faculty of Mathematics and Information Science, Warsaw University of Technology. She is one of the founders of the new specialisation - Data Science, where she conducts courses (e.g. Natural Language Processing) and projects coordinating students, scientists, and industry partners. She has several years of experience designing intelligent systems for data analysis and modelling and leading R&D teams acquired in cooperation with scientific and commercial environments (Cognitum, Asseco Poland, Allegro - the most extensive e-commerce portal in Eastern Europe, Applica, Synerise, Poznan University of Technology). Her research interests include machine learning in practical applications, especially semantic understanding of data: text and image, semantic data modelling, recommendations, and deep multimodal learning.  


Basic travel information can be found here:

- Public Transport System in Warsaw wtp.waw.pl
- Prices of the tickets in Warsaw public transport (zone 1) wtp.waw.pl
- Application how to get to warszawa.jakdojade.pl
- Polish Railway rozklad-pkp.pl
- Bus connections polskibus.com

Chopin Airport in Warsaw. The website includes an interactive arrival/departure timetable and information on transportation.
To reach WUT, take the bus 188 in front of the Airport Exit gates and get off at the METRO POLITECHNIKA stop. When you get off from the bus, you will need to walk about 950 m to PL. POLITECHNIKI 1.

Use only official companies (see below). Outside of Terminal 2 airport, there is a taxi rank. There, you will find official taxis waiting to take customers.
- City Taxi +48 22 848 88 88
- Wawa Taxi +48 22 333 44 44
- Ele Taxi +48 22 811 11 11
- MPT Taxi +48 22 19191
- Sawa Taxi +48 22 644 44 44
- Eco Car +48 123456789

There is also Uber and FreeNow. Receipts are available.

To reach WUT from Central Railway Station, take the tram 10 in front of the CRS and get off at the Pl. POLITECHNIKI stop. 

We recommend that participants use portals such as booking.com and airbnb to look for short term rentals in Warsaw. 

Warsaw is the capital of Poland and its biggest city. The city was a witness of wars and the Warsaw Rising during the II World War (in 1944), during which it was almost completely destroyed. Rebuilt after the war, it has kept its historical atmosphere in the Old Town (which is included in the World Heritage List by UNESCO). Nowadays, Warsaw is Poland's business center with headquarters of many international companies.

The city is divided into 18 districts. WUT Main Campus is located in the most central district called "Śródmieście".

Discover Warsaw!

We really believe that you will be fine with just English but just in case you want to feel more secure, you can find here some of the Polish words and names you will probably encounter on your way.

Warsaw University of Technology - Politechnika Warszawska
student card - legitymacja studencka
Dean's Office / Student office - dziekanat
dean - dziekan
Main Building of WUT - Gmach Główny PW
faculty - wydział
dormitory - akademik / dom studencki
examination period - sesja
room / office - pokój
opening hours - godziny otwarcia
student - student
library - biblioteka
canteen - stołówka
bus - autobus
tram - tramwaj
ticket - bilet
public transport monthly card - karta miejska
airport - lotnisko
Central Railway Station - Dworzec Centralny
City center - Centrum
Good morning / Good afternoon - Dzień dobry
Goodbye - Do widzenia
Thank you - Dziękuję
Please - Proszę
Excuse me - Przepraszam
Sorry, I don't speak Polish - Przepraszam, nie mówię po polsku
I don't understand - Nie rozumiem
Do you speak English? - Czy mówisz po angielsku?



Participants who successfully complete the course and present their results will be awarded a certificate of participation in the ENHANCE Winter School with 4 ECTS equivalence.


Data Literacy: Winter school, blended course
Timing: 6-10 February 2023 in Warsaw + 13 February – 12 March 2023 online via MS Teams
Tutors: Anna Cena, Anna Wróblewska,
Course level: B.Sc and M.Sc
Course type: hybrid mode with on-site in Warsaw and online via MS Teams
ECTS: 4 credit points
Organizing unit: Warsaw University of Technology

The learning activities are organized as follows:

► 40h of onsite learning:
When: 6-10 Feb. 2023
Where: at Warsaw University of Technology
Who: WUT staff
Learning activities: Lectures + workshops (20h) and project (20h) (in international teams)
Scope: Introduction to Python (focused on data analysis), machine learning, NLP, text processing

► 40h of on-line learning:
When: 2-4 weeks after onsite part, e.g. 13 Feb. – 12 Mar. 2023
Where: online, MS Teams
Who: WUT + TUB + UPV staff
Learning activities: online lectures + workshops (20h) and continuation of the project (20h)
Online lecture: 2-4h (TBD) by prof. Tim Teubner (TUB) – topic: web scrapping
Online Presentation: (2h) + online supervision (2-4h) by UPV, prof. Felix Buendia, prof. Jose V. Benlloch-Dualde – topic: Educational Learning Analytics
Project tutoring and supervision:

► 20h of teams selfwork and reporting – asynchronous mode Project:  
One challenge-based team project
International teams, 3-4 students per team
Concerns data analysis
Starting from the first day of WSiDL, finishes at the end of WSiDL
With defined milestones (e.g. one at Feb. 10th – presentation of current state of the work, at the end of the WSiDL (e.g. 12 Mar.) – presentation of the results)
Report from the project work – one per team


Follow the link below to register for Winter School:


Contact Ms Anna Smulska from Warsaw University of Technology:


Warsaw University of Technology / Center for International Cooperation

pl. Politechniki 1 room. 234
00-661 Warsaw, Poland

In association with
Warsaw Design Factory

National Agency for Academic Exchange

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