Unit 5: Dynamic Programming
In this unit, we will study another popular computer science algorithmic paradigm called the dynamic programming. Dynamic programming, like the divide-and-conquer method, solves problem by combining solutions to sub-problems. Dynamic programming typically applies to optimization problems in which a set of choices must be made in order to arrive at an optimal solution. It is effective when a given sub-problem may arise from more than one partial set of choices. We will look into problems, such as the longest common subsequence and the knapsack problem, to explain the key ideas behind dynamic programming.
Completing this unit should take you approximately 7 hours.
5.1: Introduction to Dynamic Programming
5.2: Dynamic Programming
5.3: The Knapsack Problem
5.4: Dynamic Programming Examples