Interdisciplinary Graduate Course in Python Programming at the Escuela de Verano de Postgrado 2026
26 - January - 2026
Between January 19 and 23, 2026, the summer course Introducción a la Programación en Python was held in the context of the Escuela de Verano de Postgrado 2026 as part of the graduate training activities offered by the Facultad de Ciencias Químicas. The course was taught by Prof. Stefan Vogt-Geisse and brought together graduate students from a broad range of academic programs, including chemistry, microbiology, engineering, linguistics, and sociology, highlighting the increasingly interdisciplinary role of programming in contemporary research.
Throughout the week, participants were introduced to the fundamentals of Python programming, with a strong emphasis on practical skills relevant to data analysis and scientific workflows. Course contents included core Python concepts, control structures, functions, data structures, file input/output, data processing with Pandas, and data visualization using Matplotlib. The structure of the course combined short theoretical introductions with extensive hands-on sessions, allowing students to immediately apply newly acquired concepts.
A key feature of the course was its focus on research-oriented applications rather than purely abstract programming exercises. This approach enabled students from diverse disciplinary backgrounds to see how computational tools can be adapted to their specific research questions and methodologies.
On the final day, students presented mini programming projects directly related to their ongoing PhD research. These projects ranged from data processing and visualization pipelines to small, purpose-built analysis tools tailored to individual research needs. In several cases, students also explored the use of AI-based tools to support code development, data exploration, and analytical workflows. Participants emphasized that the tools and concepts acquired during the course will contribute significantly to improving the efficiency, reproducibility, and analytical depth of their current and future research work.
Overall, the course demonstrated the value of interdisciplinary computational training and reinforced Python’s role as a unifying tool across the natural sciences, engineering, and the social sciences. It also highlighted the commitment of QCMM to supporting graduate education by providing students with high-level programming and analytical skills that are increasingly essential for addressing the challenges of the contemporary scientific and technological landscape.
