Gain insights into essential algorithms, delve into recursion, backtracking, and graph theory, and enhance your problem-solving skills in C++ to confidently tackle complex challenges.

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 C++.

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 C++. 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 C++

## Shortest path tree
Previously, we discussed several algorithms to find the shortest paths from a single-source vertex $s$ to every other vertex of the graph by constructing the shortest path tree rooted at $s$. The shortest path tree specifies two pieces of information for each node $v$ in the graph:

- $dist(v)$: This is the length of the shortest path from $s$ to $v$.
- $pred(v)$: This is the second-to-last vertex in the shortest path from $s$ to $v$.


# Shortest path tree
Previously, we discussed several algorithms to find the shortest paths from a single-source vertex $s$ to every other vertex of the graph by constructing the shortest path tree rooted at $s$. The shortest path tree specifies two pieces of information for each node $v$ in the graph:

- $dist(v)$: This is the length of the shortest path from $s$ to $v$.
- $pred(v)$: This is the second-to-last vertex in the shortest path from $s$ to $v$.


Learn about the history and evolution of all-pairs shortest paths algorithms.

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

Introduction to All-Pairs Shortest Paths

Shortest path tree