Master fundamental algorithms and data structures essential for efficient programming and problem-solving. This course provides a comprehensive foundation in algorithmic thinking, complexity analysis, and the implementation of core data structures used in computer science and software development.
Arrays, linked lists, trees, and graphs
Efficient sorting and searching methods
Big O notation and performance analysis
Graph traversal and pathfinding algorithms
Big O notation, time and space complexity analysis
Array operations, resizing, and dynamic array implementations
Singly, doubly linked lists, and circular linked lists
Stack and queue operations, implementations, and applications
Recursive algorithms, divide and conquer, backtracking techniques
Bubble sort, selection sort, insertion sort, and analysis
Merge sort, quick sort, heap sort, and comparison
Linear search, binary search, and search optimizations
Hash table implementation, collision resolution, applications
Tree terminology, binary tree traversals, and operations
BST operations, balancing, and AVL trees introduction
Heap properties, heapify, priority queue implementations
Adjacency matrix, adjacency list, graph properties
Breadth-first search (BFS) and depth-first search (DFS)
DP concepts, memoization, and classic DP problems
Comprehensive project and introduction to advanced algorithms
This course is currently being developed. Weekly content, coding assignments, and practical exercises will be added progressively. Stay tuned for updates!