An algorithm is a step-by-step procedure for solving a problem or accomplishing a task. In programming, algorithms are the foundation of how we process and manipulate data efficiently.

Why Learn Algorithms?

Understanding algorithms is crucial for several reasons:

1. Problem Solving: Algorithms provide proven approaches to common problems
2. Efficiency: Knowing which algorithm to use can dramatically improve your code’s performance
3. Interviews: Algorithm knowledge is essential for technical interviews
4. Better Code: Understanding algorithms helps you write more efficient, elegant code

What We’ll Cover

In this unit, we’ll explore fundamental algorithms implemented in JavaScript:

• Searching Algorithms: How to find elements in data structures

  • Linear Search: Simple, sequential searching
  • Binary Search: Efficient searching in sorted arrays

• Sorting Algorithms: How to arrange data in order

  • Bubble Sort: Simple but inefficient sorting
  • Selection Sort: Finding minimums iteratively
  • Merge Sort: Efficient divide-and-conquer sorting
  • Quicksort: Fast, recursive sorting

Algorithm Complexity

Each algorithm has a time complexity that describes how its performance scales with input size. We express this using Big O notation:

• O(1): Constant time - always the same speed
• O(log n): Logarithmic - very efficient for large datasets
• O(n): Linear - time grows proportionally with input
• O(n log n): Log-linear - efficient sorting algorithms
• O(n²): Quadratic - gets slow with larger inputs

Understanding these complexities helps you choose the right algorithm for your use case.

Lessons in this unit: