Recursion Backtracking and Dynamic Programming in Python

Course Overview

This course provides an overview of the fundamental concepts of algorithmic problems, focusing on recursion, backtracking, dynamic programming and divide and conquer approaches. It covers topics such as recursion and recursive methods, stack memory and heap memory overview, Fibonacci numbers, factorial function, tower of Hanoi problem, linear search approach, binary search algorithm, selection algorithms, Hoare's algorithm, quickselect algorithm, median of medians algorithm, the secretary problem, binary numbers, logical operators and shift operators, checking even and odd numbers, bit length problem, Russian peasant multiplication, backtracking, n-queens problem, Hamiltonian cycle problem, coloring problem, knight's tour problem, maze problem, Sudoku problem, dynamic programming, knapsack problem, rod cutting problem, subset sum problem, Kadane's algorithm, longest common subsequence (LCS) problem, optimal packing, bin packing problem, divide and conquer approaches, dynamic programming and divide and conquer method, sorting in O(NlogN) with merge sort, the closest pair of points problem, substring search algorithms, brute-force substring search, Z substring search algorithm, Rabin-Karp algorithm and hashing, Knuth-Morris-Pratt (KMP) substring search algorithm, common interview questions (Google, Facebook and Amazon), anagram problem, palindrome problem, integer reversion problem, dutch national flag problem, trapping rain water problem, algorithms analysis, running time analysis with big O (ordo), big Ω (omega) and big θ (theta) notations, complexity classes, polynomial (P)and non-deterministic polynomial (NP)algorithms. The course will also cover the implementation of these problems from scratch in Python.