Mastering data structures and algorithms is key to becoming a successful software engineer. Learn more about data structures and algorithms in this comprehensive guide.
Here’s what we’ll cover:
Data structures and algorithms are a critical part of a computer science education, though not something that most bootcamps graduates or self-taught people will know very well.
This guide will serve as an introduction to data structures and algorithms, especially for those who do not have formal education in the space.
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A data structure is a method of organizing data in a virtual system. Think of sequences of numbers, or tables of data: these are both well-defined data structures. An algorithm is a sequence of steps executed by a computer that takes an input and transforms it into a target output.
Together, data structures and algorithms combine and allow programmers to build whatever computer programs they’d like. Deep study into data structures and algorithms ensures well-optimized and efficient code.
There are many algorithms for different purposes. They interact with different data structures in the same computational complexity scale. Think of algorithms as dynamic underlying pieces that interact with static data structures.
The way data is expressed in code is flexible. Once you understand how algorithms are built, you can generalize across different programming languages. In a sense, it’s a bit like knowing how a related family of languages work syntactically. Once you glimpse the fundamental rules behind programming languages and their organizing principles, you can more easily switch between the different languages and learn each faster.
Common data structures you’ll see across different programming languages include:
Each of these has its own computational complexity for associated functions like adding items and finding aggregate measures such as the mean for the underlying data structure.
Some common categories of algorithms are:
It’s important to learn data structures and algorithms properly so you can understand the organizing principles behind web development and programming work.
Follow these steps to ensure your learning is as efficient as your algorithms will be.
This guide will walk you through data structures and algorithms in Python and their different implementations. It’ll walk through tangible examples of Python’s built-in data structures, as well as examples of Python algorithms from search to sorting.
Top companies and others looking to hire web developers and software engineers might ask data structures and algorithm interview questions in order to try to qualify and sift through large pools of candidates.
One example is the now-infamous whiteboard interviews, where interview candidates are asked to write out an algorithm and how it interacts with a data structure by hand, without the use of a computer.
Anyone looking for a software engineering job should be ready for these interview situations and be ready to understand data structures and algorithms in order to be prepared.
Here is a list of resources to help you learn data structures and algorithms.
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