Introduction

Why Study Algorithms?

Algorithms are the foundation of all software. Every program you write — whether it sorts a list, searches a database, or finds a route on a map — relies on well-understood algorithms. Learning them makes you a better programmer at every level.

  • Speed matters -- A naive O(n²) sort on 1 million elements takes seconds. An O(n log n) sort takes milliseconds. The algorithm is the difference.
  • Interview ready -- Algorithms are the core of technical interviews at every top tech company.
  • Problem solving -- Algorithm design teaches systematic thinking: how to decompose problems, identify patterns, and reason about correctness.
  • Universal knowledge -- These algorithms run on every language, every platform, every architecture.

The Canon

The algorithms in this course are not academic curiosities. They are the ones that power real software:

  • Merge sort is used in Python's sorted() and Java's Arrays.sort().
  • Quick sort underlies C's qsort and C++'s std::sort.
  • BFS finds shortest paths in Google Maps and social network friend suggestions.
  • Dijkstra's algorithm powers GPS navigation and network routing protocols.
  • Dynamic programming is used in sequence alignment (bioinformatics), spell correction, and compiler optimization.

What You Will Learn

This course contains 15 lessons organized into 5 chapters:

  1. Sorting -- Bubble sort, selection sort, insertion sort, merge sort, and quick sort. Understand the trade-offs between O(n²) and O(n log n) algorithms.
  2. Searching -- Linear search for unsorted data, binary search for sorted data. The power of O(log n).
  3. Data Structures -- Stack (LIFO), Queue (FIFO), and Linked List. The building blocks for more complex algorithms.
  4. Graphs -- Breadth-first search (BFS), depth-first search (DFS), and Dijkstra's shortest path algorithm.
  5. Dynamic Programming -- Memoization, the Fibonacci sequence, and the Longest Common Subsequence problem.

Each lesson explains the algorithm, shows the code, and gives you an exercise to implement it.

Let's get started.

Next →