Motivated by problems that arise in a variety of disciplines, this course examines concepts and develops skills in solving computational problems. Topics covered include abstraction (how to hide details), modularity (how to decompose problems), data structures (how to efficiently organize data), and algorithms (procedures for solving problems). Laboratory assignments are implemented using object-oriented programming techniques.
said it was good
called it a layup
Know how to code? Try contributing to Layup List!
| Name | Reviews |
|---|---|
| Timothy Pierson | 27 |
| Robert Drysdale | 13 |
| Alberto Quattrini Li | 5 |
| Christopher Bailey-kellogg | 5 |
| Prasad Jayanti | 2 |
| Christopher Bailey-Kellogg | 0 |
| David Kotz | 0 |
| Michael Casey | 0 |
Login to write a review.