Algorithms

We try get a better understanding of what exactly and algorithm is

Why We Need to Care About Algorithms

Algorithms are sets of instructions that computers follow to solve problems or complete tasks. Here's why understanding algorithms is crucial:

Efficiency

Algorithms determine how quickly and effectively tasks are completed. Knowing how algorithms work helps us choose tools and technologies that optimize performance.

Decision Making

From search engine results to loan approvals, algorithms play a role in shaping our digital experiences. Understanding how algorithms make decisions fosters responsible use and critical evaluation.

Problem Solving

Algorithms are at the heart of innovation. By understanding how problems are broken down and solved algorithmically, we can approach challenges with a more analytical and creative mindset.

How to Analyze Algorithms: Running Time and Big O

At the core of algorithm analysis lies running time, which refers to the time it takes an algorithm to execute based on the size of its input data. Here's where Big O notation comes in:

Big O Notation

This mathematical tool expresses the growth rate of an algorithm's running time as the input size increases. Understanding Big O allows us to compare the efficiency of different algorithms for a specific task. Optimizing Our Algorithms

The goal of algorithm design is often to find the most efficient solution for a given problem. Here are some key strategies for optimization:

While we won't delve into specifics here (refer to dedicated blog posts for Insertion Sort, Merge Sort, Bubble Sort, and Big O), it's important to understand how different sorting algorithms perform in terms of running time:

By understanding algorithms, their analysis, and optimization techniques, we become more empowered users of technology.