Techniques and principles of algorithm design including divide-and-conquer and greedy algorithms.

Complexity (worst and average case) analysis and their associated asymptotic notations (Theta, Big O, Omega).

Iterative sorting algorithms: Bubble sort, insertion sort.

Recursive sorting: merge sort, quick sort, heap sort.

Sorting in linear time: counting/radix sort.

Decision tree analysis: N*logN bound on comparison-based sorting.

Algorithms for graph problems: Shortest path (Dijkstra), minimum spanning trees (MST algorithms: Kruskal, Prim).

Hashing.

Discussion on NP-class problems (e.g. Travelling Salesman Problem).