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, strings, pointer-based data structures and searching and sorting algorithms. The laboratories reinforce the lecture topics and develops essential programming skills. Estimated course enrolment: ~150
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, lists, maps. Program structure: control flow, functions, classes, objects, methods. Algorithms and problem solving. Searching, sorting, and complexity. Unit testing. Floating-point numbers and numerical
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promising candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and
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characterize large quantities of candidate molecules, calibrating theoretical models with experimental data, predicting promising candidates with computational tools and machine learning algorithms, and