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This lecture introduces the course organization, including in-person and online sessions, exercise sessions, and the availability of course materials on Moodle. The instructor explains the use of Jupyter Notebook for experimenting with Python code, sharing notes, and homework assignments. Students will learn about algorithms, interpolation, integration, solving equations, and linear systems. Practical examples include analyzing springs under forces and solving differential equations. The lecture covers approximation theory, discretization, and the digital resolution of linear systems, with applications in fluid dynamics and structural analysis.
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