Data Structures and Algorithms

This course introduces students to the fundamental concepts of data organization and algorithmic problem-solving in computer science. The course covers a variety of data structures such as arrays, linked lists, stacks, queues, trees, graphs, and hash tables, as well as key algorithms used for searching, sorting, and manipulating data. Students will learn how to select and implement the appropriate data structures and algorithms for different types of problems, with a focus on performance, efficiency, and scalability.

Upon successful completion of this course, students will be able to:

• Understanding Fundamental Data Structures: Students will gain a thorough understanding of core data structures such as arrays, linked lists, stacks, queues, trees, and graphs, and learn how they are used to organize and manage data effectively.
• Analyzing Algorithm Efficiency: Learn how to evaluate and compare the efficiency of algorithms in terms of time complexity and space complexity using Big-O notation, enabling students to choose optimal algorithms for different problem scenarios.
• Implementing Algorithms for Searching and Sorting: Gain proficiency in implementing fundamental algorithms such as binary search, quicksort, mergesort, and other searching and sorting techniques, while understanding their trade-offs and performance characteristics.
• Applying Data Structures to Real-World Problems: Develop problem-solving skills by applying appropriate data structures and algorithms to a variety of real-world problems, ensuring that solutions are efficient, scalable, and maintainable.

These outcomes aim to equip students with the foundational knowledge and skills needed to work with data structures and algorithms in software development, preparing them for advanced topics in computer science, programming, and systems design. The course prepares students for careers in software engineering, data analysis, and technical problem-solving.