What is a greedy algorithm? It is difficult to describe what it is, but we generally say an algorithm is greedy if it builds up a solution in small steps, choosing a decision at each step myopically to optimize some underlying criterion. One can design different greedy algorithms for the same problem, but all optimizing locally to reach an optimal solution. When a greedy algorithm succeeds in solving a nontrivial problem optimally, it implies something interesting and useful about the structure of the problem itself; there is a local rule that one can use to construct optimal solutions. A greedy algorithm will give us a guaranteed close to optimal solution always. 
The two basic methods, **the greedy algorithm stays ahead** and **exchange argument**, will be used to show that a greedy algorithm will produce an optimal solution to a problem. By //the greedy algorithm stays ahead//, we mean that if one measures the greedy algorithm's progress step by step, then it is better than any other algorithm at each step, and thus produces an optimal solution.
By //exchange argument//, : one considers any possible solution to the problem and gradually transforms it into the solution found by the greedy algorithm without affecting its quality. Some of the most well-known applications of the greedy algorithm: shortest paths in a graph, the minimum spanning tree problem, and the construction of Huffman codes for performing data compression. A more complex application, the Minimum-Cost Arborescence Problem will further extend our notion of what a greedy algorithm is.

This section was introductory and pretty easy to read through. I would give it a scale of 9/10.