Algorithms
Searching, sorting and complexity analysis.
Algorithms is taught here in 3 lessons, running from Complexity and Big-O in practice through to Graph algorithms: BFS, DFS and shortest paths. Each lesson takes one topic, shows the working code, and links onward to the next, so the course can be read straight through in order.
| Track | Computer Science Fundamentals |
| Lessons | 3 |
| Level | Beginner |
| Reading time | about 39 minutes |
| Prerequisites | None beyond being able to open a text editor |
Lessons
- Complexity and Big-O in practiceReading growth rates off real loops, measuring instead of guessing, and knowing where Big-O stops predicting runtime.
- Sorting and searchingWhich comparison sort to reach for, why stability matters, and binary search written so it cannot loop forever.
- Graph algorithms: BFS, DFS and shortest pathsRepresenting a graph, traversing it breadth-first or depth-first, and choosing between Dijkstra, Bellman-Ford and A*.
More in Computer Science Fundamentals
Data Structures Computer Networks Operating Systems Character Encodings Hashing & Checksums Data Formats Dates & Time Regular Expressions
FAQ
How long does the Algorithms course take?
It has 3 lessons, about 39 minutes of reading. Expect roughly twice that if you type out and run every example.
Do I need prior experience for Algorithms?
No. This is the first course in Computer Science Fundamentals, so it starts from the beginning and assumes no background.
What should I read after Algorithms?
Continue with Data Structures (3 lessons), the next course in Computer Science Fundamentals.
Last refreshed 2026-09-18.