This page contains content I have created for various lecture courses that I have taught.
Data Structures II - Author: Paul Robinette
This course covered advanced data structures and algorithms such as hash tables, maps, B-trees, Dijkstra's algorithm, acyclic graph checks, minimal spanning trees and big-O analysis.
Parallel Programming - Author: Paul Robinette
Parallel programming focused on teaching technologies such as Boost threads, MPI, CUDA and Go as well as methods to parallelize programs. The slides below are not complete as some content was inherited from a previous class.
Neural Networks - Author: Paul Robinette
Supervised, unsupervised and reinforcement learning were all covered in this course. The specific neural networks and algorithms taught include perceptron, ADALINE, multi-layered perceptron, backpropagation training, recurrent neural networks, radial basis functions, q-learning, TD-learning and markov models.
Introduction to Robotics Class - Authors: Ryan Meuth, Paul Robinette
We covered a very broad section of robotics, including path planning, machine vision and motor control. Below is a link to the class website that contains all of our lectures. I created approximately half of the lectures and assignments.
Some updates created during the second run of the course are in the folder below. All changes were made by me.