As a developer, mastering the concepts of algorithms and being proficient in implementing them is essential to improving problem-solving skills. This course aims to equip you with an in-depth understanding of algorithms and how they can be utilized for problem-solving in Python.

Starting with the basics, you'll gain a foundational understanding of what algorithms are, with topics ranging from simple multiplication algorithms to analyzing algorithms. Then, you’ll delve into more advanced topics like recursion, backtracking, dynamic programming, and greedy algorithms. You'll also learn about basic graph algorithms, depth-first search, shortest paths, minimum spanning trees, and all-pairs shortest paths. 

By the end of this course, you'll have acquired a wide range of skills that will significantly enhance your ability to solve problems efficiently in Python. Through this course, not only will you improve your coding skills, but you will also gain confidence in tackling complex problems.

Mastering Algorithms for Problem Solving in Python

## Introduction to backtracking
The prototypical backtracking problem is the classical **n queens problem**, first proposed by German chess enthusiast Max Bezzel in 1848 (under his pseudonym “Schachfreund”) for the standard $8 × 8$ board and by François-Joseph Eustache Lionnet in 1869 for the more general $n × n$ board. The problem is to place $n$ queens on an $n × n$ chessboard so that no two queens are attacking each other. For readers not familiar with the rules of chess, this means that no two queens are in the same row, the same column, or the same diagonal.

# Introduction to backtracking
The prototypical backtracking problem is the classical **n queens problem**, first proposed by German chess enthusiast Max Bezzel in 1848 (under his pseudonym “Schachfreund”) for the standard $8 × 8$ board and by François-Joseph Eustache Lionnet in 1869 for the more general $n × n$ board. The problem is to place $n$ queens on an $n × n$ chessboard so that no two queens are attacking each other. For readers not familiar with the rules of chess, this means that no two queens are in the same row, the same column, or the same diagonal.

Learn about the classic n queens problem and its solution using backtracking.

Getting Started

Introduction to Algorithm

Recursion

Backtracking

Dynamic Programming

Greedy Algorithms

Prove Your Skills: A Five-Chapter Assessment

Basic Graph Algorithms

Depth-First Search

Minimum Spanning Trees

Shortest Paths

All-Pairs Shortest Paths

Pushing Your Limits: A Comprehensive Assessment

Wrapping up

N Queens

Introduction to backtracking