Covered: • Introduction to algorithmic thinking and design • Analysis of algorithms (proof techniques, asymptotic notation) • Divide & conquer: recursive design techniques and solving recurrences • Greedy algorithms: Coin changing, Interval scheduling, Fractional knapsack, Huffman codes • Dynamic programming: Top-down approach, Bottom-up enumeration, Optimal substructure, Optimal coin changing, Minimum cost path in grid, Multi-stage graphs, Unbounded knapsack, 0/1 knapsack, Edit distance, Longest common subsequence, Dynamic time warping • Computational geometry: Convex hulls (properties, Gift-wrap algorithm, Graham-scan algorithm), Plane-sweep algorithms (closest pair, line intersections), Range search methods (kD trees, Quadtrees) • Graphs: Topological ordering, Minimum spanning trees, Single-source and All-pair shortest paths • Backtracking: combinatorial search and generation • String matching: Rabin-Karp algorithm, Knuth-Morris-Pratt algorithm, Boyer-Moore algorithm.