Recursion Backtracking and Dynamic Programming in Python

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 91 lectures (9h 9m) | Size: 1.33 GB
Learn Recursion, Backtracking, Divide and Conquer Methods and Dynamic programming via Examples and Problems in Python

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What you’ll learn:
Understanding recursion
Understand backtracking
Understand dynamic programming
Understand divide and conquer methods
Implement 15+ algorithmic problems from scratch
Improve your problem solving skills and become a stronger developer

Requirements
Basic Python

Description
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?

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

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!

Who this course is for
This course is meant for newbies who are not familiar with algorithmic problems in the main or students looking for some refresher
Anyone preparing for programming interviews or interested in improving their problem solving skills

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