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Data Structures and Algorithms Curriculum


Module 1: Introduction to Data Structures and Algorithms

  • Introduction to the course
  • Importance of data structures and algorithms in programming
  • Big O notation and time complexity analysis

Module 2: Basic Data Structures

  • Arrays and their manipulation
  • Linked lists: Singly and doubly linked lists
  • Practical: Implementing basic operations on arrays and linked lists
  • Coding exercise: problems using arrays and linked lists

Module 3: Stacks and Queues

  • Introduction to stacks and queues
  • Array-based and linked list-based implementations
  • Practical: Implementing stack-based and queue-based algorithms

Module 4: Trees and Binary Trees

  • Introduction to trees and binary trees
  • Binary tree traversals: Inorder, Preorder, Postorder
  • Practical: Implementing binary tree traversals
  • Coding exercise: Checking if a binary tree is a valid binary search tree

Module 5: Binary Search Trees (BST)

  • Properties of binary search trees
  • Operations on BST: Insertion, deletion, searching
  • Balancing BSTs: AVL trees and Red-Black trees
  • Practical: Implementing BST operations
  • Coding exercise: Finding the successor of a node in a BST

Module 6: Heaps and Priority Queues

  • Introduction to heaps
  • Min-heaps and max-heaps
  • Priority queue implementation using heaps
  • Practical: Implementing a priority queue
  • Coding exercise: Merging K sorted arrays using a min-heap

Module 7: Hashing and Hash Tables

  • Introduction to hashing
  • Hash functions and collision resolution strategies
  • Practical: Implementing a basic hash table
  • Coding exercise: Finding the first non-repeated character in a string using hashing

Module 8: Graphs and Graph Algorithms

  • Introduction to graphs: Types and representations
  • Breadth-First Search (BFS) and Depth-First Search (DFS)
  • Shortest path algorithms: Dijkstra's and Bellman-Ford
  • Practical: Implementing BFS and DFS
  • Coding exercise: Finding the shortest path between two nodes using Dijkstra's algorithm

Module 9: Sorting Algorithms

  • Comparison-based sorting algorithms: Bubble, Selection, Insertion, Merge, Quick
  • Non-comparison-based sorting: Counting and Radix sort
  • Practical: Implementing various sorting algorithms
  • Coding exercise: Implementing merge sort

Module 10: Dynamic Programming

  • Introduction to dynamic programming
  • Overlapping subproblems and optimal substructure
  • Practical: Solving problems using dynamic programming approach

Module 11: Advanced Topics (Optional)

  • Advanced data structures: Trie, Segment Tree, Disjoint Set Union
  • Advanced algorithms: Floyd-Warshall, A* Search
  • Practical: Implementing advanced data structures and algorithms
  • Coding exercise: Solving a range sum query problem using a segment tree

Module 12: Review and Project

  • Review of key concepts and algorithms
  • Final coding project: Implementing a real-world problem using data structures and algorithms
  • Presentation and discussion of projects