Computer Science, Second Cycle, Bioinformatics, AI and Network Biology for Precision Medicine and Health, 7.5 Credits

This course offers an in-depth, hands-on approach to applying computational techniques such as bioinformatics, machine learning, network medicine, and AI to integrate and analyse molecular, clinical, and pre-clinical data. You will learn how to handle diverse types of data – from genomic sequences, molecular data to clinical outcomes – and implement advanced modelling approaches using tools and algorithms that can process such data and find general predictive patterns. Emphasizing practical experience, you will engage in real-world data analysis tasks, either on your own hardware or via online platforms, allowing you to develop technical skills in data integration, predictive modelling, and visualization. In this interdisciplinary course, you will collaborate with students from fields such as biomedicine, biology, chemistry, and other life sciences, gaining experience and insights into how data science can be applied in healthcare. An important focus is on cultivating effective inter-professional communication and collaboration between diverse disciplines, preparing you for collaborative project work in complex, real-world environments.

ECTS Credits

7.5 Credits

Level of education

Second cycle, has only first-cycle course/s as entry requirements (A1N)

School

School of Science and Technology