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This lecture introduces the concept of numerical differentiation, explaining the need for it in various numerical problems such as solving differential equations and optimization. It covers forward differences, Taylor's expansion, Big O notation, and the interpretation of finite differences. The lecture also discusses how fast forward differences approach the true value, truncation error, and round-off error, emphasizing the importance of choosing an optimal grid size to minimize errors.