Introduction – Notion of algorithm – Fundamentals of algorithm problem solving – Important Problem types - Fundamentals of Analysis of algorithm efficiency: Analysis Framework – Asymptotic notations – Mathematical Analysis of non-recursive algorithms – Analysis of recursive algorithms: Substitution method, Recursion tree method and Master theorem

Brute force: Selection sort, Bubble sort, Sequential search, Closest pair and Convex Hull problems – Divide and conquer: Analysis of binary search, quick sort and merge sort – Multiplication of largest integers - Strassen’s matrix multiplication

Dynamic Programming: Computing a Binomial coefficient – Optimal Binary Search Tree (OBST) – 0/1 knapsack problem and memory function – Warshall’s and Floyd’s algorithm – Greedy Technique: Minimum spanning tree – Analysis of Prim’s and Kruskal algorithm – Shortest path: Analysis of Dijkstra’s algorithm – Huffman Trees

Flow Networks – Ford Fulkerson method – Maximum Matching in Bipartite Graphs – String matching: Naïve String matching algorithm – Knuth Morris Pratt algorithm – Rabin karp algorithm

Limitations of algorithm power: Lower-Bound Arguments – Decision Trees – P, NP and NP complete problems – Backtracking: n-queens problem – Hamiltonian circuit problem – Branch and bound: Assignment problem – Knapsack problem – Travelling salesman problem – Approximation Algorithms for NP–hard problems (knapsack problem)