Best Data Structures & Algorithms Courses in 2026 (Ranked)

Last updated: October 2026. Written by Josh Hutcheson. See our review methodology.

Data structures and algorithms (DSA) are the core of every technical interview and the foundation of a computer science education. But “the best DSA course” depends on why you need it: preparing for coding interviews, studying the theory properly, or learning in a specific language. This guide ranks the courses that do each job best. We opened every course on 17 October 2026 to confirm it is live and to record its rating, size and last update, and we read what learners on Reddit recommend before choosing. We have not taken every course end to end; where we describe a course, it is from its syllabus, its listing and what learners report.

See our top interview pick on Udemy →

What are data structures and algorithms?

A data structure is a way of organizing information so a program can use it efficiently: arrays, linked lists, hash tables, stacks, queues, trees, heaps and graphs are the common ones. An algorithm is a step-by-step method for solving a problem with that data, such as searching, sorting or finding the shortest path. The two go together: the right structure makes an algorithm fast, and the wrong one makes it slow.

Interviewers test DSA because it shows whether you can reason about efficiency, usually expressed in Big-O notation, and not only write code that runs. A good course spends as much time on when and why to use a structure as on how to build it.

Big-O in one paragraph

Big-O notation describes how an algorithm’s running time or memory grows as the input grows. O(1) means constant: looking up a key in a hash table takes about the same time whether it holds ten items or ten million. O(log n) grows slowly, like binary search halving a sorted list. O(n) grows in step with the input, like scanning a list once. O(n log n) is the cost of efficient sorting, and O(n²) is what nested loops over the same data usually cost. Almost every interview answer ends with a Big-O statement, so every course on this page teaches it first. Space complexity, the memory an algorithm needs, is described the same way and is asked about almost as often.

The best DSA courses at a glance

Ratings, counts and lengths as shown on each course page on 17 October 2026. Coursera ratings are averaged across the courses in a specialization. Udemy listed both Udemy courses at $14.99 for new learners that day.

How we chose these courses

We looked at what ranks for DSA courses, what Class Central and other review sites recommend, and what learners on r/learnprogramming, r/learnpython and r/csMajors actually say helped them. Then we opened each listing. Our criteria: the course must cover the full core (Big-O, the standard structures, sorting, searching, recursion, graphs and dynamic programming); it must include practice, not just lectures; it must carry a strong rating across many learners or come from a university with real authority in the subject; and each pick must serve a different need.

We earn a commission on some links. Several of the best options on this page are free, and we say so, including two that earn us nothing at all.

1. Best for interviews: Master the Coding Interview: Data Structures + Algorithms (Andrei Neagoie)

Andrei Neagoie’s course is the one we would hand to most people with an interview coming up. On 17 October 2026 it had 4.7 stars from 40,909 ratings and 271,195 students, with 19.5 hours of video last updated in March 2026. Rather than covering every textbook structure, it focuses on what interviews test: Big-O analysis, arrays, hash tables, linked lists, stacks and queues, trees and graphs, recursion, sorting, and dynamic programming, with interview-style exercises along the way.

The code is in JavaScript, but the explanations are language-neutral and most learners follow along in Python or Java. Neagoie also teaches the same course inside his Zero To Mastery academy.

Best for: developers and bootcamp graduates preparing for technical interviews. Watch for: it is a foundation; pair it with daily practice on a curated problem list.

Check the price on Udemy →

2. Best free academic course: Algorithms, Part I (Princeton)

Princeton’s Algorithms, Part I, taught by Kevin Wayne and Robert Sedgewick, is the standard rigorous introduction. Coursera showed 4.9 stars from 12,151 reviews and 1,471,436 learners enrolled on 17 October 2026. It covers union-find, analysis of algorithms, stacks and queues, elementary sorts, mergesort, quicksort, priority queues, symbol tables, balanced search trees, geometric applications of binary search trees and hash tables, with programming assignments in Java. Part II continues with graphs and strings.

Every feature of the course is free, including the graded assignments. Coursera notes that it does not offer a certificate at all. (This page used to say only the first module was free to preview; that was wrong.) Plan for about five weeks at 10 hours a week.

Best for: computer science students and self-learners who want depth, not shortcuts. Watch for: it is demanding, it assumes basic Java, and the assignments take real time.

Take Algorithms, Part I free on Coursera →

3. Best pattern-based prep: Grokking the Coding Interview Patterns (Educative)

Educative’s Grokking course teaches interview problems as 28 recurring patterns, such as two pointers, sliding window, fast and slow pointers, merge intervals and topological sort, so you learn to recognize which approach a new problem needs. Its listing on 17 October 2026 showed 1,125 lessons across 31 modules, 579 quizzes, 17 AI mock interviews, 85 hours of material and a 4.9 rating, with solutions in Python, Java, JavaScript, C++, C# and Go. It is text-based and interactive: you read and run code in the browser instead of watching video.

Best for: developers who know the basic structures and want to get faster at recognizing patterns. Watch for: it is part of an Educative subscription, so use it intensively for a few weeks. Our Grokking the Coding Interview review covers pricing and alternatives.

View Grokking on Educative →

4. Best conceptual university course: Algorithms Specialization (Stanford)

Tim Roughgarden, a Stanford computer science professor since 2004, teaches this four-course specialization, which emphasizes understanding over low-level implementation. It covers divide-and-conquer, sorting and searching, randomized algorithms, graph search, shortest paths, data structures such as heaps and hash tables, greedy algorithms, dynamic programming, and NP-completeness. Coursera showed 4.8 stars from 6,002 reviews and 134,699 learners on 17 October 2026.

Its weekly programming assignments can be done in any language you like, which makes it a good fit if you do not want to work in Java. A Coursera subscription is needed for the certificate.

Best for: learners who want to understand why algorithms work, in their own language. Watch for: it is lighter on interview-style practice than the courses above, so add a problem list.

View the Stanford specialization on Coursera →

5. Best long structured path: Data Structures and Algorithms Specialization (UC San Diego)

UC San Diego’s six-course specialization is the closest thing online to a full university sequence. It includes about 100 programming challenges with instant feedback, algorithmic puzzles, and capstone-style applications such as analyzing a large social network and assembling a genome. Coursera showed 4.6 stars from 16,777 reviews and 385,677 learners on 17 October 2026, and estimates about five months at 10 hours a week.

Best for: learners who want a long, guided program and a shareable certificate. Watch for: it is a multi-month subscription commitment, so it is not the right choice for last-minute interview prep.

View the UC San Diego specialization →

6. Best for JavaScript developers: JavaScript Algorithms and Data Structures Masterclass (Colt Steele)

If you work in JavaScript, Colt Steele’s course teaches DSA in your own language. It had 4.7 stars from 31,310 ratings and 174,380 students on 17 October 2026, with 21.5 hours of video updated in January 2026. Steele covers Big-O, problem-solving approaches, recursion, searching and sorting, and the major structures from linked lists to graphs, with many exercises.

Best for: front-end and full-stack developers who think in JavaScript. Watch for: if you interview in Python or Java, a language-neutral course serves you better.

Check the price on Udemy →

7. Best for deep fundamentals: Mastering Data Structures and Algorithms using C and C++ (Abdul Bari)

Abdul Bari’s course is a long-standing favorite for learners who want to build every structure from scratch. It had 4.6 stars from 60,702 ratings and 257,595 students on 17 October 2026, with 76 hours of whiteboard-style explanations. Implementing everything in C and C++ forces you to understand memory and pointers rather than relying on built-in collections.

Watch for: it was last updated in June 2025 and it is very long. Treat it as a thorough foundation, not a quick refresher.

Check the price on Udemy →

8. Best interactive Python option: Learn Data Structures and Algorithms in Python (Boot.dev)

Boot.dev’s DSA course has you build the structures yourself in Python inside the browser, with chapters on Big-O and the math behind it, sorting, linked lists, binary trees, graphs and more. It showed 4.6 stars from 1,644 ratings, 44,676 students, 127 lessons and about 32 hours of content on 17 October 2026. It is part of a Boot.dev subscription; we have no affiliate relationship with Boot.dev. Our Boot.dev review covers the platform.

9. Best free interview path: NeetCode

NeetCode is the resource Reddit recommends most for interview DSA. In a well-upvoted r/learnprogramming answer to a bootcamp graduate asking where to learn DSA for interviews, the top reply called NeetCode’s practice list the gold standard. NeetCode offers two DSA courses: Algorithms and Data Structures for Beginners (about 25 hours) and Advanced Algorithms (about 25 hours), plus the NeetCode 150 problem list with video solutions. Much of it is free, with a paid Pro tier. We have no affiliate relationship with NeetCode.

Best for: daily interview practice on a budget. Watch for: the list assumes you can already program comfortably.

10. Best with reviewed projects: Data Structures and Algorithms Nanodegree (Udacity)

Udacity’s nanodegree is the most structured paid option and the only one here where a person reviews your work. On 17 October 2026 Udacity listed it at 47 hours, 4.7 stars from 530 reviews, updated 11 August 2026, with more than 100 algorithm and data structure challenges in Python and four reviewed projects: breaking down open-ended coding problems, implementing linked lists, trees, maps and heaps from scratch, choosing and analyzing algorithms for given problems, and an A* route planner that finds shortest paths on a map.

It is sold by subscription, and Udacity was advertising a 40% new-user discount on 17 October 2026. It makes sense if deadlines and feedback are what you need to finish; otherwise the cheaper courses above cover the same material. Our Udacity DSA review covers cost and prerequisites.

See the Udacity DSA nanodegree →

Other good free resources

Princeton’s Algorithms, Part II: the free sequel to pick 2, covering undirected and directed graphs, minimum spanning trees, shortest paths, maximum flow, radix sorts, tries, substring search, regular expressions, data compression and intractability. Coursera showed 4.9 stars from 2,050 reviews on 17 October 2026, about six weeks at 10 hours a week, and no certificate. The Last Algorithms Course You’ll Need: ThePrimeagen’s course on Master.dev (the former Frontend Masters) is free to watch in full and teaches Big-O, the core structures and searching and sorting in TypeScript; Class Central rates it among the best interview-focused courses. LeetCode Explore: LeetCode’s free topic cards walk through arrays, linked lists, trees and more with practice problems.

MIT OpenCourseWare 6.006: MIT publishes the full Introduction to Algorithms course (Spring 2020) with lectures, notes and problem sets. It is excellent and mathematical. freeCodeCamp: publishes free DSA learning resources and full-length video courses on YouTube. Structy: a DSA course you can start free, designed to raise difficulty gradually; Reddit learners recommend it to people who find LeetCode too steep. For video channels, see our list of the best YouTube channels for DSA.

Princeton vs Stanford vs UC San Diego: the university options compared

Choose Princeton if you are comfortable in Java and want rigor at no cost. Choose Stanford if you want to understand why algorithms work and prefer to code in Python or another language. Choose UC San Diego if you want the most practice problems and a long, structured program with a certificate at the end.

Free vs paid: which should you choose?

Go free if you learn well on your own, do not need a certificate, and mainly need to fill gaps: Princeton, MIT and NeetCode will take you a long way. Go paid if you want a single guided path, pattern-focused interview training, or the commitment that comes from having paid. The paid options here are inexpensive compared with what passing a technical interview is worth, so the real cost is your time. Pick the format you will finish.

Master the Coding Interview vs Grokking vs NeetCode

These three come up most often for interview preparation, and they suit different people. Master the Coding Interview is a video course: best if you are learning the structures for the first time and want them explained in order, at a one-off price. Grokking is a text-based, interactive course organized by pattern: best if you already know the structures and need to get fast at recognizing which technique a problem needs, and if you read faster than you watch. NeetCode is a curated problem list with video solutions and free courses: best as your daily practice, alongside either of the others.

A common and effective combination is one of the first two for concepts and NeetCode’s list for practice.

What each option costs

How to choose the right DSA course

Which language should you learn DSA in?

Use the language you will interview or work in. Python is the most common interview choice because it is concise and has built-in lists, dictionaries and sets, so you spend less time on syntax. Java is the language of Princeton’s course and of AP Computer Science A, and it makes types explicit. C and C++ teach you what happens in memory. JavaScript is fine if it is your working language. The concepts are identical; switching languages later is easy.

If language is your deciding factor, this is where each pick fits:

The core topics, and how fast common operations are

Whichever course you choose, it should cover these structures. This table shows the typical cost of common operations, which interviewers expect you to know:

Beyond structures, the algorithm families to know are sorting and binary search, recursion and backtracking, breadth-first and depth-first search, shortest paths, greedy algorithms, and dynamic programming. For dynamic programming in particular, see our guide to dynamic programming courses.

An eight-week DSA study plan

At five to ten hours a week, this covers the core in two months. Learners on Reddit stress two habits: revisit topics a few days after you learn them (spaced repetition), and do not wait too long before looking at a solution when you are stuck, then re-solve the problem yourself a few days later.

What a coding interview actually tests

A typical technical screen gives you 45 to 60 minutes for one or two problems. Interviewers watch four things: whether you ask clarifying questions and confirm the inputs and edge cases, whether you can reach a working solution, whether you can analyze its time and space cost and improve it, and whether you explain your thinking as you go. The data structure is usually the key to the better solution: most first attempts are brute force, and a hash map, a heap or two pointers turns them into something efficient.

That is why courses that only explain structures are not enough on their own. Practice out loud, on a timer, and finish every problem by stating its Big-O. Our guide to how to crack a coding interview walks through each stage of the process.

Mock interviews

Solving problems alone is different from solving them while someone watches. Before real interviews, do at least a few mocks: Grokking includes 17 AI mock interviews with scoring rubrics, friends or study partners can take turns as interviewer, and many university career centers run practice sessions. Record yourself if you have no partner; listening back shows where your explanation goes quiet.

Common mistakes when studying DSA

Watching instead of solving. Hours of video feel productive but do not build the skill. Aim for more time solving than watching. Grinding random problems. Without a list organized by pattern, you repeat easy wins and miss whole topics. Memorizing solutions. If you cannot rebuild a solution a week later, you memorized it; redo problems you got wrong. Skipping complexity analysis. Interviewers always ask for it. Switching courses constantly. Pick one main course and one problem list, and finish them.

Books worth owning

Princeton’s course is based on Sedgewick and Wayne’s Algorithms, Fourth Edition, and its companion site algs4.cs.princeton.edu is free. Learners on Reddit still mention Gayle Laakmann McDowell’s Cracking the Coding Interview alongside NeetCode for interview prep. A book is a good complement to a course because it is easier to revisit one topic quickly.

Should you learn DSA first or start with LeetCode?

Both camps exist on Reddit: some people learn the structures first, others learn by solving problems and looking up what they need. The approach that works for most beginners is a hybrid. Learn one topic from a course, then immediately solve five to ten problems on that topic. Courses alone leave you unable to apply what you learned; problems alone, without the concepts, turn into memorizing answers.

How many problems should you solve?

Curated lists are far more efficient than solving problems at random. Blind 75 and Grind 75 cover the most common patterns in about 75 problems; NeetCode 150 extends that to 150 with video explanations. Working carefully through one of these, and being able to explain each solution, prepares most candidates for typical interviews. People targeting the most selective companies often go to 300 or more, with an emphasis on medium-difficulty problems. If you are deciding whether to pay for LeetCode, see Is LeetCode free?

Is data structures and algorithms hard?

In an r/csMajors thread about DSA classes, the most upvoted reply put it simply: DSA is easy to learn and hard to master. The concepts are within reach of anyone who can program and handle basic algebra. Competitive-programming-style problems and applying the right technique under interview pressure are what take time. If a course feels too fast, drop to a gentler one such as Structy or Boot.dev, then come back.

How long does it take to learn data structures and algorithms?

With basic programming skills and five to ten hours a week, most people cover the core structures and algorithms in six to ten weeks, as in the plan above. Interview readiness takes longer, usually two to four months, because speed comes from the number of problems you have worked through and reviewed. A university course such as UC San Diego’s runs about five months at 10 hours a week. If you are starting from zero programming experience, learn a language first; our guide to the best coding courses is the place to start.

Is DSA still worth learning when AI can write code?

Yes, for two practical reasons. First, coding interviews at most companies still test DSA directly, usually without AI assistance. Second, AI tools produce code faster than they produce good judgment: knowing that a nested loop is quadratic, that a lookup belongs in a hash map, or that a recursive solution will overflow the stack is what lets you spot when generated code is slow or wrong. The amount of memorization you need may shrink; the need to reason about efficiency has not.

Do DSA certificates matter?

Searches for free DSA courses with a certificate are common, but certificates carry little weight with employers for this subject, because the interview itself tests the skill. Udemy, Coursera specializations, Boot.dev, Educative and Udacity issue certificates of completion; Princeton’s free courses do not. If you are a student, a strong grade in your university’s data structures course and a record of solved problems say more than any certificate.

Do you need DSA for non-FAANG roles?

Less than people assume, but more than zero. Many companies outside big tech still ask a coding question or two built on arrays, hash maps, strings and simple recursion. Front-end and full-stack roles usually go lighter on algorithms than back-end, infrastructure and systems roles. Learn the fundamentals and the main patterns; skip the most advanced topics unless your target companies are known for them.

DSA for high school and college students

If you are a college student, your university’s data structures course is usually the most important class for internship interviews, and the courses above are the best way to prepare for it or catch up after it. Princeton’s free course follows a similar syllabus. High school students taking AP Computer Science A meet arrays, lists and basic algorithms in Java; our guide to coding classes for high schoolers covers where to start before a full DSA course.

What to study after DSA

For junior roles, DSA plus a solid project portfolio is usually enough. For mid-level and senior roles, interviews add system design: how you would build a service such as a URL shortener or a news feed at scale. Our review of Grokking the System Design Interview covers one popular option, and our guide to coding interview courses covers the rest of the interview loop.

Which DSA course should you take?

Interview soon: Master the Coding Interview, then a curated problem list. Free and rigorous: Princeton’s Algorithms, Part I. Pattern drilling: Grokking. University-style path in any language: Stanford’s specialization. JavaScript: Colt Steele. C and C++: Abdul Bari.

Start with our top pick →

Related guides: how to crack a coding interview, best coding interview courses, best computer science courses, best Java courses, and best coding courses if you are still learning to program. These fundamentals are also what a forward deployed engineer interview tests.

Frequently asked questions

What is the best data structures and algorithms course?

For interview preparation, Andrei Neagoie’s Master the Coding Interview: Data Structures + Algorithms on Udemy (4.7 stars from 40,909 ratings). For free academic depth, Princeton’s Algorithms, Part I on Coursera (4.9 stars from 12,151 reviews), which is entirely free. For pattern-based practice before interviews, Educative’s Grokking the Coding Interview Patterns.

Can I learn data structures and algorithms for free?

Yes. Princeton’s Algorithms, Part I and Part II on Coursera are free in full, though they do not offer certificates. MIT OpenCourseWare publishes the complete Introduction to Algorithms (6.006) course, NeetCode offers free beginner and advanced courses, and freeCodeCamp publishes free DSA video courses.

Which programming language is best for DSA?

Use the language you will interview or work in. Python is the most popular choice for interviews because it is concise. Java is the language of Princeton’s course and AP Computer Science A. C or C++ forces you to understand memory and pointers. The concepts are the same in every language.

How long does it take to learn data structures and algorithms?

Most people can learn the core structures and algorithms in six to ten weeks of steady study. Being ready for coding interviews usually takes two to four months, because it depends on how many problems you practice, not on how many videos you watch.

Is data structures and algorithms hard?

The concepts are learnable with basic programming skills and a little math. Applying them quickly to unfamiliar interview problems is the hard part, and it takes practice. Students often describe DSA as easy to learn and hard to master.

How many LeetCode problems should I solve?

Quality matters more than count. Curated lists such as Blind 75, Grind 75 and NeetCode 150 cover the common patterns; working through one of them carefully, and revisiting problems you got wrong, prepares most people for typical interviews. Candidates aiming at the most selective companies often go to 300 or more.

Do I need DSA for web development jobs?

Less than for back-end or systems roles. Many companies still ask basic questions about arrays, hash maps, strings and simple recursion in interviews, so learn the fundamentals and the main patterns even if your day-to-day work rarely uses advanced algorithms.

Are paid DSA courses worth it?

They are worth it for structure, clear explanations and organized practice. Everything you need is available free, so pay only if a course keeps you consistent. A Udemy course on sale costs less than a meal; subscriptions such as Educative or Coursera are better used intensively for a month or two.

Do DSA courses give certificates?

Udemy, Coursera specializations, Educative and Boot.dev give certificates of completion, but employers rarely care about them. Princeton’s free Coursera course gives none. What counts in hiring is solving problems in the interview.