I learned how to implement Dijkstra's algorithm by applying it to a dataset of cities. Using object-oriented practices, I coded it so that the user can select different cities, and the program responds.
In Data Structures, we learned that nearest-neighbor approximation can estimate the solution for the travelling salesman problem, so we implemented it.
I also wrote a visualization tool for finding the minimum spanning tree. This solution uses Kruskal's algorithm.
Here is a tool to demonstrate Huffman encoding.