Best resources to learnData Structures & Algorithms

Introduction to Algorithms (MIT 6.006)

Modeling computational problems and solving them with core algorithms and data structures: sorting, hashing, binary trees, heaps, graph search, shortest paths and dynamic programming. 32 lecture videos, notes, problem sets and exams with solutions teach asymptotic analysis and algorithm design.

Design and Analysis of Algorithms (MIT 6.046J)

Intermediate algorithms after 6.006: divide-and-conquer, randomization, dynamic programming, greedy algorithms, network flow, amortization, complexity and cryptography. 39 lecture videos, notes, problem sets and exams with solutions train learners to design efficient algorithms and prove their correctness and running time.

Data Structures

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures. A few examples of questions that we are going to cover in this class are the following: 1. What is a good strategy of resizing a dynamic array? 2. How priority queues are implemented in C++, Java, and Python? 3. How to implement a hash table so that the amortized running time of all operations is O(1) on average? 4. What are good strategies to keep a binary tree balanced? You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space!

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Algorithms, Part I

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms. All the features of this course are available for free. People who are interested in digging deeper into the content may wish to obtain the textbook Algorithms, Fourth Edition (upon which the course is based) or visit the website algs4.cs.princeton.edu for a wealth of additional material. This course does not offer a certificate upon completion.

Algorithms, Part II

📚Books(3)

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The Algorithm Design Manual, 3rd Edition

Two-part book: a practical treatment of design techniques illustrated by war stories from real consulting projects, then a catalog of roughly seventy-five classic problems with the known algorithms and implementations for each. Trains you to recognize when a task reduces to a solved problem.

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Introduction to Algorithms, 4th Edition (CLRS)

The standard algorithms reference, covering asymptotic analysis, sorting, hash tables, red-black trees, dynamic programming, graph algorithms, flows, matchings, online algorithms and NP-completeness with formal proofs. Gives you the vocabulary and tools to state and prove running-time bounds precisely.

advanced🇬🇧

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Algorithms (Jeff Erickson, free textbook)

Open-access UIUC textbook on recursion, backtracking, dynamic programming, greedy algorithms, graphs, maximum flow and NP-hardness, with hundreds of exercises. Emphasis falls on how a solution is discovered and proved correct, so you can design and justify unfamiliar algorithms.

advanced🇬🇧

🌐Websites(5)

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takeUforward

Striver's SDE Sheet, a curated list of roughly 190 coding-interview problems grouped by topic, from arrays and linked lists to graphs and dynamic programming, with linked video and written solutions. Gives a structured practice plan for technical interview preparation.

Visualgo

Interactive visualizations of data structures and algorithms built by Steven Halim at the National University of Singapore, animating sorting, trees, graphs, and shortest paths step by step so learners can trace how each algorithm changes state.

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visualgo.net

Visualgo.net is an interactive visualization platform for learning data structures and algorithms, offering animated, step-by-step demonstrations of core structures (arrays, lists, stacks, queues, trees, graphs) and algorithms with explanations.

cp-algorithms.com

Open-source translation of the Russian e-maxx algorithm compendium, with articles on number theory, combinatorics, graph algorithms, string processing, and geometry. Each entry pairs a derivation with tested C++ code you can adapt for contest problems.

LeetCode

Online judge with thousands of algorithm and data-structure problems sorted by difficulty, topic and company, plus timed contests, discussion threads and study plans. Regular practice builds fluency with common interview problem patterns and writing correct, efficient code under time pressure.