Recent Blog Posts
In this post, we’ll take a tour through three key algorithmic strategies that go beyond the fundamentals: recursion, backtracking, and graph algorithms. We’ll start with a high-level overview of each approach, then dive into examples to show how they work in practice. Whether you’re building up your problem-solving toolkit for technical interviews or just looking to expand your understanding of what’s possible with code, these patterns will give you new ways to think about complex challenges and the confidence to tackle them.
In this post, we’ll break down what Big-O notation actually is (no scary math, I promise), why it matters more than you might think, and how it affects your everyday work as a developer. We’ll look at how it helps measure the performance of algorithms, how to use it when making design decisions, and some common time complexities you’ll see in the wild - explained with real-world scenarios that make sense.
In this post, we’ll break algorithms down into byte-sized chunks (see what I did there?), explaining them in the most beginner-friendly way possible. You don’t need any advanced math skills to understand these concepts, just a little curiosity and an open mind. We’ll cover some of the most common types of algorithms – sorting and searching - along with examples to make them easier to grasp.
In this post, we’re breaking down the mystery of data structures, exploring the essential building blocks that will make your coding experience smoother and more efficient. We'll cover different types of data structures, including when and why you’d want to use them. By the end, you'll have a solid understanding of how to choose the right structure for your code, helping you write smarter, faster programs with less frustration.
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