SKILLS: Complexity analysis | Algorithm design | Asymptotic notation
Learners will be able to explain what algorithms are and why they matter; distinguish formal and informal analysis; evaluate time and space using asymptotic notation across best/average/worst cases; set up and solve recurrences; prove correctness of iterative algorithms with loop invariants; analyze classic sorting methods; and design, implement, and compare solutions using core paradigms such as divide-and-conquer (with case studies like merge sort and quicksort), while communicating “tight”, machine-independent complexity bounds.
Our curriculum matches modern standard practices to provide exceptional training milestones.
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