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To me the whole point of a university course is to learn part of the theoretical knowledge you would not learn spontaneously by practicing. That includes way more than just algorithms and datastructures.

For example, a good knowledge of language theory will prevent engineers from creating scripting languages that cannot be parsed. Probabilities are everywhere in machine learning. Many engineers work with by-products of operational research and need to understand the theory behind them to make them efficient. Complex numbers and trigonometry (quaternions etc.) are needed to build even basic 3D engines. Recent probabilistic data structures such as hyperloglog are being integrated into modern database systems. Good understanding of operating systems is useful for security and parallel programming...



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