Class Programming for Biosciences I

The curricular unit Programming for Biosciences I introduces the foundations of computing and programming within the study programme in Computational Biomedicine and Artificial Intelligence. Its scope includes the design, interpretation, and implementation of algorithms and programs, using Python and Julia to solve problems in Medical Sciences and biosciences. The course develops skills in syntax, data types, control structures, functions, data structures, abstraction, functional and object-oriented programming, and file handling. These domains enable students to organise, process, and analyse data and develop computational solutions for biomedical problems. Due to its introductory and applied nature, the course provides an essential foundation for subsequent curricular units in data analysis, modelling, artificial intelligence, and biomedical computing, strengthening the scientific and technical coherence of the study programme.  

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1. Introduction to Computing 2. Programming Languages (Python) 3. Syntax and Semantics 4. Variables, Expressions, and Data Types 5. Input and Output 6. Control Flow Structures 7. Functions and Procedural Abstraction 8. Data Structures 9. Functional Programming

In the theoretical component, content is presented clearly through digital presentations, prepared from the relevant literature and made available in advance to encourage prior study and classroom discussion. Current scientific articles are also analysed to stimulate critical thinking and develop skills in reading and evaluating scientific literature. Classes alternate between concept presentation and discussion, encouraging active participation. In the theoretical-practical component, students complete exercises and projects of increasing complexity, aligned with the progression of the syllabus. Individual work is complemented by group activities, during and outside contact hours, promoting autonomy, collaboration, and personal development.

Guttag, J. V. (2021). Introduction to Computation and Programming Using Python: With Application to Understanding Data. MIT Press. Bezanson, J., Karpinski, S., Shah, V. B., & Edelman, A. (2017). Julia Programming for Operations Research: A Primer on Computing. Independent Publishing. Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to Algorithms. MIT Press.