With dynamic programming (DP), we can guarantee the correctness of a certain category of algorithms by systematically searching all possibilities while providing efficiency through the storage of intermediate results, which helps avoid recomputation.
During a recent online learning session, Curtis Schlak, our VP of Professional Development, provided guidance about how to classify algorithms as potential beneficiaries of dynamic programming, how to speed up certain kinds of algorithms with DP, and how to implement it in recurrence relations.
In case you missed the event live or want to revisit the session, watch a recording here.
Note: You’ll likely get the most out of this session if you’ve had some exposure to data structures (like linked list and binary tree) and algorithms (like sorting and searching).
Curtis develops and teaches our Professional Development courses, designed for software engineers looking for skills and mentorship while they move along their career paths. Learn more about our upcoming courses here.