Free online courseIntroduction to algorithms

Course Description

Welcome to "Introduction to Algorithms," a sought-after course with an outstanding 5-star rating. This comprehensive course, aimed at providing an in-depth understanding of algorithms, spans 35 hours and 19 minutes and falls under the Information Technology category, specifically focusing on Programming Logic. With an impressive array of topics and practical problem sessions, this course delivers a robust foundation in algorithms and computation.

Starting with the basics, the course introduces you to fundamental concepts in algorithms and their computational implications. The journey begins with an exploration of data structures and dynamic arrays, equipping you with the essential tools to understand higher-level algorithmic strategies.

In the early stages, you will delve into the asymptotic behavior of functions, learning to analyze and compare the efficiency of various algorithms. The course includes a practical problem session to reinforce your understanding of these concepts through double-ended problem-solving techniques.

As you progress, you will explore sets and sorting algorithms, gaining insights into how to efficiently organize and retrieve data. The topic of hashing will also be addressed, offering you a deep dive into one of the fastest data lookup methods available.

The course doesn't shy away from complex topics either. You'll engage with linear sorting algorithms and their applications, understanding their advantages and limitations. The concept of binary trees is thoroughly examined over two comprehensive parts, including a focused session on AVL trees, a type of self-balancing binary search tree.

Further along, the curriculum covers binary heaps and explores breadth-first search (BFS), a key algorithm for traversing and searching tree or graph data structures. Depth-first search (DFS) is also covered, offering another critical perspective on algorithmic problem-solving.

Weighted shortest paths, such as those solved by the Bellman-Ford and Dijkstra algorithms, are a highlight of the course. These topics are vital for anyone looking to understand pathfinding in weighted graphs. The All-Pairs Shortest Path (APSP) algorithm and Johnson's algorithm for sparse graphs are also discussed.

Dynamic programming, a method for solving complex problems by breaking them down into simpler subproblems, is covered extensively. You will learn and apply dynamic programming techniques across a variety of problems, from sequence alignment to coin change and longest common subsequence (LCS).

The course also touches on the principles of algorithmic complexity, preparing you for more advanced topics and helping you understand the boundaries and possibilities within the field of algorithmic problem-solving.

The grand finale involves a comprehensive course review and insights into the next steps in your algorithmic education. Whether you're a novice looking to get a solid grounding in algorithms or a seasoned programmer aiming to refine and expand your skills, this course offers unparalleled depth and quality.