Teaching 

Data science 

I teach an intensive two-day introduction to Data Science combining key theoretical foundations with practical implementation in Python. The course begins with the mathematical basics used in data science, including statistics, introductory calculus, and elements of optimization.

Participants then work on hands-on Python exercises using real datasets such as the Titanic dataset and housing price data. Through these examples, they explore a range of data analysis and machine learning techniques, including regression models, classification approaches, and an introduction to neural networks.

The goal of the course is to provide participants with a broad overview of modern data science methods and practical experience applying them to real-world datasets.

Green IT

I teach a course on Green IT, focusing on the environmental impact of digital technologies and strategies to design more sustainable computing systems. The course introduces key concepts such as energy consumption of IT infrastructure, carbon footprint of digital services, and lifecycle analysis of hardware and software.

Participants explore practical approaches to reducing the environmental impact of digital systems, including efficient software design, sustainable data management, and responsible use of computing resources. The course combines conceptual discussions with practical examples to help participants understand how digital technologies can be developed and used more sustainably.

Data analyst

I teach an introduction to Data Analysis, focusing on practical skills using SQL and Python. The course covers how to extract, clean, and analyze data from databases, as well as how to perform exploratory data analysis and visualization.

Participants learn how to query datasets using SQL and use Python tools such as Pandas and Matplotlib to manipulate, analyze, and visualize data. Through hands-on exercises, they develop the skills needed to transform raw data into meaningful insights for decision-making.