The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and search ...

Review of basic structures; object-oriented techniques; analysis, comparison, and design of algorithms for data structure processing; binary trees, recursion; sorting, searching methods. Prerequisites ...

Introduction to the fundamental principles of data structures and algorithms and their efficient implementation. Developing algorithmic thinking. Basic toolkit for the design and analysis of ...

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

Covers algorithms and their performance analysis, data structures, abstraction, and encapsulation. Introduces stacks, queues, linked lists, trees, heaps, priority queues, and hash tables, and their ...

An introduction to the analysis and implementation of algorithms and data structures including linear data structures, trees, graphs, hash tables, searching algorithms, sorting algorithms, ...