What is an algorithm, characteristics of good algorithms, understanding time and space complexity, Big-O, Big-Theta, Big-Omega notations, analyzing best, worst & average cases, complexity examples in real problems.

Static and dynamic arrays, memory layout, insertion & deletion operations, searching techniques, 2D arrays, strings as arrays, implementation of arrays in C/Java/Python.

Singly linked list, doubly linked list, circular linked list, operations (insert, delete, search, update), memory management, applications, comparison with arrays.

Stack operations, infix-prefix-postfix conversion, expression evaluation, recursion relationship, queue operations, circular queue, priority queue, deque, real-life applications.

Tree terminology, tree traversals (inorder, preorder, postorder), BST insertion & deletion, balanced vs unbalanced trees, threaded trees, expression trees, binary heap basics.

AVL trees, Red-Black trees, B-trees, B+ trees, heap implementation, min/max heap operations, heap sort, trie (prefix tree) introduction, practical applications in databases and OS.

Graph representation (matrix & list), BFS, DFS, shortest path algorithms (Dijkstra, Bellman-Ford), MST algorithms (Kruskal, Prim), topological sorting, graph applications in networking & AI.

Linear & binary search, bubble sort, selection sort, insertion sort, merge sort, quicksort (Lomuto & Hoare), heap sort, counting sort, radix sort, comparison of sorting complexities.

Understanding recursion, tail vs non-tail recursion, backtracking concepts, N-Queens, Sudoku solver, subset generation, maze solving algorithms.

DP fundamentals, memoization vs tabulation, common DP problems including knapsack, LIS, LCS, coin change, matrix chain multiplication.

Greedy strategy, activity selection, Huffman coding, fractional knapsack, job sequencing with deadlines, interval scheduling, greedy vs optimal solutions.

Hash tables, hash functions, collision resolution (chaining, linear probing, quadratic probing, double hashing), rehashing, real-world uses of hashing (databases, compilers).

Fast input/output, modular arithmetic, problem-solving patterns, sliding window, two pointers, prefix-sum, binary search on answer, coding contest tips.

DSA for web, mobile, AI, ML, networking, graphics, databases, blockchain, OS scheduling, interview-related applications.

Implementing all data structures, building a mini search engine, pathfinder using BFS/DFS, scheduling system using heaps, solving 100+ DSA problems.