Online course - Recursion, Backtracking and Dynamic Programming in Python by Udemy

This course is about the fundamental concepts of algorithmic problems focusing on recursion, backtracking, dynamic programming and divide and conquer approaches. As far as I am concerned, these techniques are very important nowadays, algorithms can be used (and have several applications) in several fields from software engineering to investment banking or R&D.

Section 1 - RECURSION

what are recursion and recursive methods
stack memory and heap memory overview
what is stack overflow?
Fibonacci numbers
factorial function
tower of Hanoi problem

Section 2 - SEARCH ALGORITHMS

linear search approach
binary search algorithm

Section 3 - SELECTION ALGORITHMS

what are selection algorithms?
Hoare's algorithm
how to find the k-th order statistics in O(N) linear running time?
quickselect algorithm
median of medians algorithm
the secretary problem

Section 4 - BACKTRACKING

what is backtracking?
n-queens problem
Hamiltonian cycle problem
coloring problem
knight's tour problem
maze problem

Section 5 - DYNAMIC PROGRAMMING

what is dynamic programming?
knapsack problem
rod cutting problem
subset sum problem

Section 6 - OPTIMAL PACKING

what is optimal packing?
bin packing problem

Section 7 - DIVIDE AND CONQUER APPROACHES

what is the divide and conquer approach?
dynamic programming and divide and conquer method
how to achieve sorting in O(NlogN) with merge sort?
the closest pair of points problem

Section 8 - COMMON INTERVIEW QUESTIONS

top interview questions (Google, Facebook and Amazon)
anagram problem
palindrome problem
integer reversion problem
dutch national flag problem
trapping rain water problem

In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together from scratch in Python.

Thanks for joining the course, let's get started!

Recursion, Backtracking and Dynamic Programming in Python

Course overview

Description

Similar courses