Plotly - open source library enabling you to visualize data. Not only it can be used for presentation of insightful and beautiful charts, but also you can use it to create interactive tutorials of some technical concepts. As an example, it can help you to teach, and therefore learn, traditional Machine …

Synthetic data is revolutionizing AI and testing. This talk explores how an API-first, open-source SDK enables developers to create high-fidelity, privacy-safe tabular data—better than anonymization, scalable across environments, and ready for real-world use.

Data access should not be a privilege. Whether you are a student, researcher, or developer, the …

We have tools that show what queries are executed and the time it takes. But what next? What is going on there? Is it good that it’s doing that? Will some indexes help? In this talk, I will help you decipher database query plans and give some rules of …

In the hands-on tutorial, we’ll go through various features of Streamlit and build a small lyric fetcher app based on the available dataset (which I have curated and will be sharing the link before the talk) of around 24K Billboard top-100 songs. Basic understanding of HTML, Python, and libraries …

Regex is one of the more flexible and simple ways of making the text in the structural data. I will give an overview and some examples in how it is used.

I have seen companies sell regex as AI.

Regex is an old magical tool that can turn any kind …

In this hands-on workshop, you will learn to parse wikitext from beginning to end. Using data from the German Wiktionary, we will fetch the data, parse the XML, and process the wikitext to extract linguistic content such as parts of speech, meanings, and inflections, and more.

We will cover the …

When you take interesting data from public sources, when you install a highly efficient Python library for data analysis (polars), and you start asking fundamental questions, what can possibly go wrong? Let’s find out while becoming familiar with polars, a modern data-frame library for Python.

In this course, we …

How can you improve your data pipelines? What standards should you enfornce in your project? What tools should you use? This talk is all about best practices and practical tips for building reliable, scalable and maintainable data pipelines in python!

Weather you are working on your new AI project or …

Ever wondered how to turn raw data into compelling insights? In this beginner-friendly workshop, you’ll learn the essentials of data handling, visualization, and analysis using Python. We’ll guide you through real-world datasets, introduce basic geospatial data concepts, and help you uncover interesting patterns—all with hands-on coding exercises …