The CS301 course, Data Structures, is designed to introduce students to the core concepts of data structures and their applications in solving computational problems. Students will learn various data structures, how to implement them, and their efficient use in algorithms. Emphasis will be placed on understanding the time and space complexities associated with different operations on these data structures. By the end of this course, students will be equipped to analyze and solve complex problems using appropriate data structures and algorithms.
Key Concepts Covered in the Course
In this course, students will learn the following data structures and algorithms:
Arrays: Static and dynamic arrays, multi-dimensional arrays, and operations like insertion, deletion, and searching.
Linked Lists: Singly linked lists, doubly linked lists, circular linked lists, and operations such as traversal, insertion, and deletion.
Stacks: Stack data structure, LIFO (Last In First Out) principle, push and pop operations, applications of stacks in function calls, recursion, and expression evaluation.
Queues: Queue data structure, FIFO (First In First Out) principle, enqueue and dequeue operations, types of queues such as circular queue, priority queue, and deque.
Trees: Binary trees, binary search trees (BST), AVL trees, tree traversal algorithms (in-order, pre-order, post-order), and applications like expression trees and Huffman coding.
Heaps: Min-heap, max-heap, and heap operations such as insertion, deletion, and heapify, along with the applications of heaps in sorting and priority queues.
Hashing: Hash functions, hash tables, collision resolution techniques like chaining and open addressing, and applications of hashing in search and retrieval.
Graphs: Graph representation (adjacency matrix and adjacency list), graph traversal algorithms (DFS, BFS), and applications in pathfinding, network flow, and shortest path algorithms like Dijkstra’s algorithm.
Learning Outcomes
Upon completing this course, students will be able to:
Understand and implement different types of data structures such as arrays, linked lists, stacks, queues, trees, heaps, and graphs.
Analyze the time and space complexity of various algorithms using Big-O notation.
Solve computational problems by choosing and implementing the most appropriate data structure based on efficiency.
Apply data structures in the design and implementation of algorithms for real-world problems like sorting, searching, and graph traversal.
Implement and use advanced data structures like balanced trees (AVL), heaps, and hash tables to optimize code performance.
Course Prerequisites
This course assumes that students have a basic understanding of programming and algorithms. It is recommended that students have completed introductory courses in programming (such as CS101) and algorithms (such as CS201). Familiarity with concepts like loops, conditionals, functions, and arrays is required for a successful learning experience in this course.
Course Structure and Duration
CS301 will be taught over one semester. The course consists of theoretical lectures, practical coding sessions, assignments, and exams. The structure is as follows:
Module 1: Introduction to Data Structures and Arrays
Module 2: Linked Lists and Their Applications
Module 3: Stacks and Queues
Module 4: Trees and Binary Search Trees
Module 5: Heaps and Priority Queues
Module 6: Hashing and Hash Tables
Module 7: Graphs and Graph Algorithms
Module 8: Advanced Data Structures and Algorithms
Assessment Methods
Student assessment in this course will be based on the following:
Assignments: Weekly assignments focusing on coding exercises to implement and apply different data structures and algorithms.
Mid-Term Exam: A written exam testing theoretical knowledge and problem-solving abilities related to data structures.
Final Exam: A practical exam where students will be required to implement data structures and solve problems efficiently.
Project: A final project that involves solving a real-world problem using data structures, demonstrating the practical application of concepts learned throughout the course.
Resources and Tools
The following resources will be used throughout the course:
Online coding platforms such as Codeforces, LeetCode, and HackerRank for practicing algorithms and data structures.
Text Editors and IDEs such as Visual Studio Code, IntelliJ IDEA, or Eclipse for coding assignments and projects.
Learning Management System (LMS): The course materials, assignments, and announcements will be available through the LMS.
Course textbooks and reference materials, which will be provided in class or accessible through the LMS.