Useful links for studying algorithms and data structures

Studying algorithms and data structures requires time and practice. We have compiled a selection of useful resources: articles, courses, books, and interactive platforms. Start with simple resources—visualizations and beginner-friendly books—then move on to more advanced courses and problems on platforms like LeetCode and Codeforces.

Why it is important to study algorithms and data structures

1. Code efficiency—choosing the right data structure speeds up application performance.

2. Problem-solving—the ability to analyze and optimize algorithms is critical for system and backend programming.

3. IT company interviews—algorithms and Data Structures & Algorithms problems are almost always part of the interview process.

Books and theoretical materials

Algorithms, Robert Sedgewick & Kevin Wayne
This book combines theory and practice: every solution is accompanied by complete implementations in modern programming languages, making the material useful for both students and practicing developers. Since its first edition, the book has become one of the most popular and cited sources on algorithms, translated into many languages, and has taught millions of programmers worldwide.

Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein
A fundamental work considered essential for a deep study of algorithms. The book covers a wide range of topics—from basic data structures and sorting to advanced graph algorithms and dynamic programming—combining rigorous mathematical justification with practical examples.

Grokking Algorithms, Aditya Bhargava
An excellent book for beginners, where complex algorithmic concepts are explained visually with the help of diagrams. The book emphasizes understanding the logic of algorithms and their practical application, helping even those just starting to learn programming and algorithms to easily grasp the basics.

Online courses

Algorithms, Part I by Princeton University
One of the most popular and accessible ways to learn algorithms and data structures. It includes 13 modules with assignments, covers sorting, searching, and basic data structures, is designed for intermediate-level learners, requires about five weeks at 10 hours per week, and has already enrolled over 1.4 million students. The course is free, with the option to delve deeper into materials on algs4.cs.princeton.edu.

Data Structures Fundamentals by UCSanDiegoX
This course introduces basic and advanced data structures necessary for efficient algorithmic work. The program combines theory with practical assignments in various programming languages, helping participants understand the internal mechanisms of built-in implementations and typical use cases for data structures, fostering skills that make learners more confident programmers.

Algorithms: Theory and Practice. Data Structures on Stepik
This course focuses on studying basic and applied data structures most commonly used in programming. You will learn how data structures are designed and implemented in different programming languages, practice applying them, expand your knowledge, and choose the most suitable structures for solving specific computational tasks.

Practice and training

LeetCode
A top platform for programming practice, offering thousands of problems from basic to advanced levels, the ability to solve them in various languages, and the opportunity to discuss solutions with a global community of developers. The platform is particularly useful for interview preparation and improving algorithmic skills.

HackerRank
The site offers structured courses and step-by-step tutorials on algorithms, data structures, databases, and other topics. Solutions are automatically checked, and there are rankings and achievements, which help track progress and encourage regular practice.

Codeforces
This platform specializes in competitive programming contests, where problems must be solved within a limited time. This develops not only algorithmic thinking but also the ability to make quick decisions, optimize code, and work under pressure, which is valuable for competitive and professional programming.

GeeksforGeeks
A vast knowledge library on DSA: articles, algorithm explanations with code examples, problem collections with solutions, and practical tips. This resource is ideal for deep theoretical study and reinforcing practical skills, as well as for exam and interview preparation.

Video resources

MIT OpenCourseWare — Introduction to Algorithms
A complete course of lectures on algorithms from MIT, covering fundamental topics: sorting, searching, data structures, graphs, dynamic programming, and much more. The lectures provide a deep theoretical understanding of algorithms, accompanied by examples and analysis of complex problems.

Abdul Bari YouTube Channel
Abdul Bari's channel is known for its simple and clear explanations of algorithms and data structures. The videos help understand complex concepts through visualizations and step-by-step breakdowns.

CS50 by Harvard
A famous introductory Computer Science course from Harvard, covering algorithms, data structures, software development, and the fundamentals of computational thinking. The course combines lectures, practical assignments, and projects, developing programming and analytical thinking skills.

Interactive trainers

Visualgo
An interactive online platform for visualizing algorithms and data structures. It allows users to see the step-by-step execution of algorithms on various data structures, such as arrays, lists, stacks, queues, trees, and graphs, significantly facilitating the understanding of their operation and internal mechanisms.

Big-O Cheat Sheet
A convenient reference table that systematizes information about the time and space complexity of major algorithms and data structure operations. It covers sorting, searching, tree operations, and hash tables, making it an indispensable tool for studying algorithms, preparing for interviews, and optimizing code.