This paper describes two neural network programming projects suitable for undergraduate students who have already completed introductory courses in Programming and Data Structures. It briefly outlines the structure and operation of Hopfield Networks from a data structure stand-point and demonstrates how these type of neural networks may be used to solve interesting problems like Perelman's Nine Flies Problem. Although the Hopfield model is well defined mathematically, students do not have to be very familiar with the mathematics of the model in order to use it to solve problems. Students are actively encouraged to design modifications to their implementations in order to obtain faster or more accurate solutions. Additionally, students are also expected to compare the neural network's performance with traditional approaches, in order that they may appreciate the subtleties of both approaches. Sample results are provided from projects which have been completed during the last three-year period.