# Algorithmic Problems in Python

## What you'll learn

- Understand backtracking
- Understand dynamic programming
- Understanding recursion
- Solve algorithmic problems from scratch

## Course content

- Preview01:21

## Requirements

- Basic Python

## Description

This course is about the fundamental concepts of algorithmic problems, focusing on **recursion**, **backtracking **and **dynamic programming**. 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:**

what is recursion

stack memory and recursion

factorial numbers problem

Fibonacci numbers

towers of Hanoi problem

recursion vs iteration

**Section 2:**

what is backtracking

n-queens problem

Hamiltonian cycle problem

knight's tour problem

coloring problem

NP-complete problems

**Section 3:**

what is dynamic programming

Fibonacci numbers

knapsack problem

coin change problem

rod cutting problem

In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems one by one.

The first chapter is about **recursion**. Why is it crucial to know about recursion as a computer scientist? Why stack memory is crucial in recursion? We will consider several recursion related problems such as factorial problem or Fibonacci numbers. The second chapter is about **backtracking**: we will talk about problems such as n-queens problem or hamiltonian cycles and coloring problem. In the last chapter we will talk about **dynamic programming**, theory first then the concrete examples one by one: Fibonacci sequence problem and knapsack problem.

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

## Instructor

Hi!

My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model.

Take a look at my website if you are interested in these topics!