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Data Science School 2026

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When

July 20–24, 2026

Format

Offline in Lviv

Registration deadline

July 17, 2026

Fee

Free of charge for selected applicants

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About

Data Science in 2026 is about knowing how to work with data, ask the right questions, uncover patterns, and build solutions that work in the real world.

That’s exactly what you’ll learn at Data Science School, a five-day intensive in-person program designed for students and early-career professionals who want to build a solid foundation in Data Science and gain hands-on experience solving real-world problems.

Throughout the program, participants will complete the entire Data Science project lifecycle: from data collection and analysis to building machine learning models, evaluating results, and presenting their own solutions.

In addition to lectures, the school includes practical workshops, mentorship from industry engineers, and a final project that allows participants to apply their knowledge in practice.

Who is it for

  • First- and second-year university students interested in starting a career in Data Science
  • Third- and fourth-year students in technical fields who want to grow in AI or Machine Learning
  • Master's students looking to strengthen their knowledge or transition into Data Science from another specialization
  • Junior IT professionals or interns who want to deepen their expertise in data analysis
  • Anyone with basic Python knowledge who is ready for an intensive five-day learning experience

To participate

  • Complete the registration form
  • Wait for the selection results
  • Receive an email with further instructions

What you'll gain

  • A solid understanding of the complete Data Science project lifecycle: from problem definition to presenting results
  • Practical skills in Python, Pandas, NumPy, and Jupyter Notebook or Google Colab
  • Hands-on experience in data analysis, cleaning, and visualization
  • An understanding of core Machine Learning algorithms, including classification, regression, clustering, and dimensionality reduction techniques
  • Experience working on your project under the guidance of experienced mentors
  • The opportunity to present your solution to industry experts and receive professional feedback

Event organized by

Department of Artificial Intelligence Systems, Lviv Polytechnic National University

Partners

Program

Opening & Introduction to Data
10:00 AM – 12:00 PM

Workshop: Introduction to Data Science, the structure of a DS project, basic Python, and Pandas.

1:00 PM – 3:00 PM

Hands-on session: Working with real-world datasets. Data cleaning and analysis exercises.

Day 2. Data Analysis & Visualization
10:00 AM – 12:00 PM

Workshop: Data analysis and visualization methods; Matplotlib, Seaborn, and Plotly.

1:00 PM – 3:00 PM

Hands-on session: Creating charts, dashboards, and a short data story.

Day 3. Machine Learning Fundamentals
10:00 AM – 12:00 PM

Workshop: Classification and regression. KNN, Decision Trees, and basic model evaluation metrics.

1:00 PM – 3:00 PM

Hands-on session: Building classification or regression models and evaluating their performance.

Day 4. Clustering, Feature Engineering & Modeling
10:00 AM – 12:00 PM

Workshop: Data clustering. K-Means, DBSCAN, dimensionality reduction, and basic feature engineering.

1:00 PM – 3:00 PM

Hands-on session: User/object segmentation, working with high-dimensional data, and preparing the final solution.

Day 5. Final Project & Wrap-up
10:00 AM – 3:00 PM

Final project, evaluation of results, and winners' award ceremony.

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