Course Logistics for Data Structures and Algorithm

1. Foundational Concepts:

• Abstract Data Types (ADTs)
• Big Oh Notation (Complexity Analysis)

2. Data Structures:

• Stacks (Array and Linked List Implementations)
• Queues (Array and Linked List Implementations)
• Dequeues (Double ended queues)
• Priority Queues (Array and Linked List Implementations)
• Linked Lists (Singly, Doubly, Circular)
• Trees and Tree Traversals (Preorder, Inorder, Postorder)
• Binary Search Trees
• Heaps
• M-way Trees
• Balanced Trees
  • AVL Trees
  • Red-Black Trees
• Graphs
  • Adjacency Matrix and Adjacency List Implementations (for Graphs)

3. Algorithms:

• Searching Algorithms:
  • Linear Search (for unsorted arrays)
  • Binary Search (for sorted arrays)
• Recursion and Analyzing Recursive Algorithms
• Divide and Conquer Algorithms
• Sorting Algorithms
  • Selection Sort
  • Insertion Sort
  • Merge Sort
  • Quick Sort
  • Bubble Sort
  • Heap Sort
  • Shell Sort
  • Radix Sort (also known as Bucket Sort)
• Shortest Path Algorithms (related to Graphs)
• Topological Sort (related to Directed Acyclic Graphs)

4. Advanced Concepts:

• Hashing
• Memory Management and Garbage Collection

Mid term Exam: 30 marks
Terminal Exam: 40 marks
Quizzes: 15 marks
Assignment: 15 marks

1. Algorithms 4rth Edition by Robert Sedgewick and Kevin Wayne
2. Data Structures and Algorithms in C++ by Adam Drozdek
3. Data Structures and Algorithm Analysis in Java by Mark A. Weiss
4. Data Structures and Abstractions with Java by Frank M. Carrano & Timothy M. Henry
5. Data Structures and Algorithm Analysis in C++ by Mark Allen Weiss
6. Java Software Structures: Designing and Using Data Structures by John Lewis and Joseph Chase

1. https://www.coursera.org/learn/algorithms-part1
2. https://www.algoexpert.io/
3. https://www.visualgo.net