Algorithms can be a pain in the butt to learn on your own. The subject matter is huge and pretty deep too.

Thankfully there are plenty of books written by programmers and professors that can help anyone learn. And in this guide I’ve organized a compilation of the best books covering algorithms & data structures for beginners and experienced developers alike.

If you’re completely new to algorithms and have no idea what to pick then Algorithms Unlocked is likely your best choice. It’s written for non-technical readers but does get into some technical topics about algorithm development and basic proofs. The authors also cover data structures in a lighter tone so that anyone can follow along with ease.

If you don’t have a background in stats & higher-level maths then you’ll need a way to pick up some basics. Introductory Discrete Mathematics is the #1 recommended book for programmers who aren’t great with math but need to understand logic or proofs.

Note that “discrete” is not a type of math(ie. Algebra, trig, etc). The term “discrete” describes data which is counted based on a number or detail(like red/blue or left/right) while continuous data can be measured.

This is crucial to understand if you want to build algorithms. Some of you reading this may already be comfortable with this material, and if so this book won’t be necessary.

But if you’re a self-taught programmer then you may need to fill in some gaps with discrete mathematics. And this book is the perfect reference to get started.

Both data structures and algorithms go hand in hand with programming.

In Data Structures and Algorithms Made Easy you’ll learn the fundamentals of data structures like arrays, strings, and data trees. But you’ll also learn about how algorithms work and how to write your own from scratch.

The book is currently in its 5th edition with lots of new content. It spans well over 400 pages full of information about different data structures and how these can be analyzed automatically using algorithms.

You will need a basis in mathematics for some of these exercises, but the author explains everything clear enough that anyone should be able to keep up. Every exercise uses C/C++ code so if you aren’t proficient then this book won’t be of much service.

But if you’re willing to pick up the basics of C++ as you move along then this can be a solid intro for even a complete newbie.

Understanding how to design an algorithm is just as important as knowing how to code it. The Algorithm Design Manual is for anyone who wants to create algorithms from scratch, but doesn’t know where to start.

This book is huge with **730 pages** full of examples and real-world exercises. The author covers a lot of theory but also pushes you further into the world of algorithm design concepts.

It’s an interesting read because it can be applied to beginners and experts alike. You don’t need to understand much about algorithms to get through these lessons. In fact, it’s good to put all your preconceived notions about algorithms to the side before reading through this text

There’s a lot to learn and it can be frustrating at times so hold tight and put in the effort.

If you’re patient and consistent with practice you’ll learn tips for developing algos and saving time by reusing existing code and reverse engineering other algorithms.

This is truly an incredible text for programmers of all skill levels.

What I like most about this book is the writing style. Introduction to the Design and Analysis of Algorithms covers algorithms from a non-technical standpoint looking more towards logic and reasoning skills.

You’ll learn about different problem solving techniques that can be applied to different scenarios. Each chapter covers a variety of material including real-world concepts with a basis in problem solving.

Each chapter has a recap section with an overview of the problem, the solution, and the theory behind the solution. This is really a book of puzzles with technical answers that draw from ideas related to algorithmic design.

If you’re a complete beginner just diving into the wacky world of algorithms then you can learn a lot from this book.

This is easily the best book to study the fundamentals of computer science. But it’s also one of the most expensive books in this list, so if possible try to find a used copy or an older edition.

Introduction to the Theory of Computation is a true college-grade textbook. It covers everything about computer science including detailed historic timelines and processes involved in software development.

However this is definitely a **theory book** so it will not push you further into algorithm development.

It’s typically a must-read for any computer science major who’s interested in the field. But it’s definitely not for everyone so consider if you’re really looking to understand the basics of computer science or not.

You can learn to code algorithms without being a computer science major. But it helps to understand discrete math and compsci terminology as a foundation to algorithm development.

Introduction to Algorithms should be the #1 introduction guide for anyone trying to learn algorithms. In its current 3rd edition it comes with **well over 1,000 pages** crammed with theory, practice, and everything in between.

You do need a decent level of maths to work through these exercises. You should be at least somewhat familiar with data structures, or at least be willing to Google and solve your own questions.

The topics in this book are dry but practical. The authors typically follow a formula of introducing a problem, diagrams with mathematical proofs, then the final completion with theory analysis.

Beginners who pick up this book may find themselves lost quick. It does not hold your hand or expect everyone to pick up the concepts quickly.

But this is one of the few books that truly gets into the core of algorithm development from a bird’s-eye view. Introduction to Algorithms has my highest rating and it should be at the top of your list once you’re ready to take the challenge.

The coolest thing about Algorithms Unlocked is how it covers the topic of algorithms. Part of the book explains this stuff in easy-to-understand English where live examples from the real world are analyzed and broken down for the reader.

Other parts of this book get into maths and equations to prove how certain algorithms function. It’s really a book made for non-PhD’s who want to understand the nature of algorithm development.

Note this is not really a textbook. It reads like a trade magazine or a personal introduction for folks who don’t have much of a technical background.

I would actually recommend this to complete beginners who have no background in this field. As you work through each chapter you’ll bump into concepts that you don’t understand. You can then search for related books or hit Google to find some answers.

Algorithms Unlocked will teach you how algorithms work without all the fanciful code. But it’ll also help you spot your insecurities or weak points in programming, maths, and computer science.

The Robert Sedgewick book simply titled Algorithms is beautifully written and currently in its 4th edition. This book is constantly referenced by professionals in universities teaching computer science programming.

This newest edition covers computer algorithms from a data structure perspective. You’ll learn how to sort, analyze, distribute, and process a variety of data types. These concepts can be applied to any language or any dataset regardless of server or database engine.

Plus with a copy of this book you get access to the full Java code along with fullsize diagrams and test data for practice.

The highlight of this book is how it explains data structures. You can pick up this title with little-to-no understanding of data structures and walk away feeling like a master.

With 992 pages this can be a very intimidating book to crack open. But if you have the tenacity to work through these exercises you’ll be a much better programmer for the effort.

The Little Schemer is a book covering LISP/scheme as a means of learning algorithm development.

These languages are mostly used as testing tools for new programmers just entering the computer science field. They don’t serve any real purpose other than to help you understand the fundamentals without getting bogged down in specifics.

What I love most about this book is how it breaks down mathematics and algebra. Every new concept you study about algorithms and computing can ultimately be broken down into math.

The authors expound upon theories and ideas while presenting questions & answers to the reader. You’ll learn about the basics of algorithms, statistics, data processing, and recursive functions as they apply to Scheme/LISP.

This is easily a must-read book for any practitioners who want to move forward with algorithm development. You don’t need any prior programming knowledge but it certainly helps as you move into the later chapters.

I recently covered Grokking Algorithms in a more detailed review explaining how incredible this book really is. It’s not an exaggeration to say that this book should be mandatory reading for aspiring programmers in college or even high school.

Grokking Algorithms aims to teach how algorithms work, what data structures are, and how it all ties together. But the author does this using **lots of visuals** and some fun language.

This book may feel very dense but it reads like a fun game. You’ll be introduced to new topics slowly while building on top of previous chapters.

The author clearly has a solid grasp on algorithms and how they’re currently used in modern technology.

Granted this book will not help you create practical algorithms or tell you how to write your own algo from scratch. But it will help anyone who feels hopelessly lost to come to terms with algorithms and their place in the computer science universe.

Advanced Data Structures is the only book for moving into more complex realms of data analysis. The book is almost 500 pages long with an in-depth look at how data types get implemented in modern applications.

This is not much of an algorithm development book, although many programming concepts are touched upon in these lessons. But the goal is to improve your understanding of data structures to optimize your search queries.

The book gets into varying ideas like hash tables, union-find structures, and more complex tree structures.

This book is rather pricey so I do not recommend it for everyone. You have to be ready to delve deep into data structures so it helps to already understand the basics of algorithms.

But this book can take a semi-skilled programmer and really help them shine with new techniques and mindsets for improving their own applications.

Lastly I wanna wrap with a great book that won’t be for everyone, but certainly should be. Mastering Algorithms with C covers algorithm development on the backbone of C programming.

The book has 550+ pages full of exercises and lessons covering advanced C concepts. The authors do not explain major concepts behind common algorithms or the fundamentals of algo development.

Instead they cover best practices for coding in C and building unique algorithms for a variety of purposes.

I cannot recommend this enough to anyone who’s breaking into C/C++ programming. Granted this may not be useful for everyone, such as game programmers who mostly work with visuals. But computer programmers working on software or data analysis can learn a lot from the lessons in this book.

Just make sure you already have some foundational knowledge of algorithms and at least intermediate-level C/C++ programming.

Algorithms can be infuriating if you have no idea what they are or how they work. If you’re at this level I highly recommend a copy of Grokking Algorithms which can be a fun introduction to the algo universe.

If you’re looking for something a little more practical then you can’t beat Introduction to Algorithms. It is the go-to guide for learning algorithm development and it covers every single topic you could ever want to learn.

Or for more of an in-between book check out Algorithms Unlocked. This straddles the line of non-technical teaching with some technical examples using basic algebra.

If you just keep practicing and trying to overcome roadblocks you can build solid skills in algorithm development. Learning on your own is rarely easy. But with these books you should have more than enough resources to move through the basics and even start writing your own algos.