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

Which problem is solved by almost every algorithm known for computing shortest paths from one vertex to another in a graph?

Which problem is solved by almost every algorithm known for computing shortest paths from one vertex to another in a graph?

It is unnatural to consider edges with negative weights.

The algorithms only work for directed graphs.

The algorithms do not work for undirected graphs.

What is the main issue with using negative edge weights in shortest-path problems?

What is the main issue with using negative edge weights in shortest-path problems?

What is the algorithm that results from replacing the FIFO queue in breadth-first search with a priority queue, where the key of a vertex is its tentative distance?

What is the algorithm that results from replacing the FIFO queue in breadth-first search with a priority queue, where the key of a vertex is its tentative distance?

What is the time complexity of the Bellman-Ford algorithm?

What is the time complexity of the Bellman-Ford algorithm?

The same vertex is processed multiple times.

Distances are not discovered in increasing order.

What is the reason for Dijkstra's algorithm being sometimes slow in practice?

What is the reason for Dijkstra’s algorithm being sometimes slow in practice?

Reinforce your understanding of shortest paths and their applications in problem solving.

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

Quiz: Shortest Paths