Course Information

Course Description

This comprehensive undergraduate course provides fundamental understanding of data structures and algorithmic design principles emphasizing computational efficiency and software engineering best practices. Students develop proficiency in design analysis and implementation of abstract data types including arrays linked structures trees graphs and hash tables. The curriculum emphasizes algorithm development methodologies time complexity analysis space optimization techniques and practical coding standards for professional software development. Students gain experience with algorithm design paradigms including divide-and-conquer dynamic programming greedy algorithms and graph traversal methods ensuring solid foundation for advanced computer science coursework and industry applications.

Learning Outcomes

Upon successful completion of this course students will demonstrate ability to:

• Design and implement fundamental data structures including arrays linked lists stacks queues trees and graphs with appropriate memory management
• Analyze algorithmic performance using Big-O notation for time and space complexity evaluation
• Apply appropriate data structure selection strategies based on problem requirements and performance constraints
• Implement advanced sorting algorithms including merge sort quick sort and heap sort with comparative analysis
• Develop efficient search algorithms using binary search techniques and tree traversal methods
• Construct and manipulate binary search trees with insertion deletion and balanced tree operations
• Design and implement graph algorithms including shortest path algorithms and traversal techniques
• Apply recursive programming techniques and divide-and-conquer algorithm design paradigms

Course Outline