Class notes and slides

I post the class slides here, they appear usually after the class, I encourage you not to depend on the slides but to take old fashioned notes, because the material will be easier to learn that way. Class notes are an amalgamation of my own slides and slides made by Janet Peterson and John Burkart.

Algorithms and Design

Lecture in PDF format
The slides discuss algorithm efficiency, brute force algorithms for sorting and searching, a transform and conquer algorithm for searching, decrease and conquer algorithms for sorting and finding a fake coint; a greedy algorithm for coin changeing, divide and conquer algorithms for sorting, searching, large integer multiplication and matrix multiplication. These lecture notes were originally prepared by Janet Peterson and slightly edited by Peter Beerli.

Random Processes

Lecture in PDF format
The slides introduce probability, calculation of probability for combined events, and short exposition of random numbers (historically and with matlab). Introduction of probability density function, cumulative density functions, examples with dice (regular and cheated ones).

Graphs

Lecture in PDF format
The slides introduce graphs and their representation in software, exploration of finding one or all path on a graph, finding the number of components, finding the shortest path between two points, traveling salesman problem etc.

Data mining: Clustering, Decision trees

Lecture in PDF format
The slides introduce clustering methods and how to use and construct decision trees, and towards the end give glimpse into machine learning.