Gain insights into algorithms and their implementation for problem-solving in Python. Learn about recursion, dynamic programming, greedy algorithms, and graph algorithms to enhance coding proficiency and problem-solving skills.

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

## Merge-sort algorithm and its recursive structure     
**Merge-sort** is one of the earliest algorithms designed for general-purpose stored-program computers. The algorithm was developed by John von Neumann in 1945 and described by him in detail in a publication with Herman Goldstine in 1947 as one of the first non-numerical programs for the EDVAC. It works as follows:
1. Divide the input array into two subarrays of roughly equal size.
2. Recursively merge-sort each of the subarrays.
3. Merge the newly-sorted subarrays into a single sorted array.

# Merge-sort algorithm and its recursive structure     
**Merge-sort** is one of the earliest algorithms designed for general-purpose stored-program computers. The algorithm was developed by John von Neumann in 1945 and described by him in detail in a publication with Herman Goldstine in 1947 as one of the first non-numerical programs for the EDVAC. It works as follows:
1. Divide the input array into two subarrays of roughly equal size.
2. Recursively merge-sort each of the subarrays.
3. Merge the newly-sorted subarrays into a single sorted array.

Understand the efficiency and effectiveness of the merge-sort algorithm.


Merge-sort

Understand the efficiency and effectiveness of the merge-sort algorithm.

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

Merge-sort

Merge-sort algorithm and its recursive structure