Welcome Gophers! In this course, we are going to be covering some of the most popular sorting and searching algorithms and how you can implement them in Go.
What You’ll Learn
This course is split into two main sections: sorting algorithms and searching algorithms. For each algorithm, we follow the same two-part structure:
- Algorithm Overview — We’ll break down how the algorithm actually works, its time and space complexity, and when you’d want to use it in the real world.
- Implementation in Go — We’ll build the algorithm step-by-step in Go, test it, and make sure it actually works.
Sorting Algorithms
We’ll cover five of the most important sorting algorithms:
- Quick Sort — The go-to general purpose sorting algorithm that uses divide-and-conquer
- Bubble Sort — A simple algorithm that’s great for understanding the basics
- Insertion Sort — Fantastic for small or nearly-sorted datasets
- Merge Sort — A stable, predictable O(n log n) sort
- Heap Sort — Sorts using a max-heap data structure with no extra memory
Searching Algorithms
Then we’ll tackle four essential searching algorithms:
- Depth-First Search — Explores graphs by going as deep as possible first
- Breadth-First Search — Explores graphs level by level, great for shortest paths
- Binary Search — Lightning-fast search on sorted arrays
- Tree Search — Searching through binary search trees
Prerequisites
You should have a basic understanding of Go before diving in. If you’re brand new to Go, I’d recommend checking out the Beginner’s Guide to Go first.
You don’t need any prior algorithms or computer science knowledge — we’ll explain everything from scratch.
Let’s Go!
Right, that’s enough preamble — let’s dive into our first algorithm!