8 Best Data Structures and Algorithms Courses [2026]

Search for a data structures and algorithms course today and you'll get a wall of university extension landing pages that hide their prices, a Coursera hub with hundreds of uncurated results, and an affiliate listicle that loves courses that pay the most commission. (Not that I'd ever be biased...)

So I went through the course pages and pulled the numbers (verified August 2026, links included).

And yes, the Berkeley Extension does charge $1,045 for 30 hours of class time... it's a traditional university extension course, what do you expect.

How I judged these

Three questions, in order of importance:

1. Do you write code, or do you watch someone else write code?
2. What does it cost?
3. Who is it best for?

Boot.dev: Learn Data Structures and Algorithms (in Python)

Learn Data Structures and Algorithms in Python is 32 hours across 126 lessons, nearly all of which have you writing Python in the browser and passing tests. It covers Big-O analysis, sorting, stacks, queues, linked lists, binary trees, red-black trees, hashmaps, tries, graphs, BFS/DFS, and finishes with P vs NP. It's rated 4.6 from 1,482 reviews with 42,042 students as of August 2026. It's also our course, so note the inherent bias...

If you finish it and want more, Data Structures and Algorithms 2 picks up with the stuff most shorter courses skip: Dijkstra's, Bellman-Ford, heaps, A* search, dynamic programming, edit distance, and linear programming. Another 22 hours, 63 lessons.

Both sit in the middle of our backend development path, so the DSA you learn is connected to the systems work that comes before and after it, rather than floating in a vacuum.

There are no lecture videos to zone out to. You read a short explanation, then you implement the thing. Boot.dev's overall Trustpilot rating is 4.8 from 215 reviews, and one review sums up the approach:

"The biggest strength of the platform is that it teaches you to think like a programmer instead of just memorizing syntax."

-- Scott Ott, Trustpilot review

The cons:

• The interactive lessons require a paid membership ($59/month or $399/year, 30-day money-back guarantee). All content is free to read and watch, but just reading/watching a DSA course removes most of the value... so it's mostly paid, to be fair.
• It's Python only. If you need to interview in Java or C++, you'll be translating.
• The certificate is a completion certificate with a public verification URL, but it's not an accredited credential. (Same as almost everything else on this list.)

NeetCode: for your interviews

NeetCode is Navdeep Singh's interview-prep platform (I'm a huge fan), and it's very upfront about what it is: you're here to pass coding interviews, so let's drill the patterns that appear in coding interviews.

The DSA lineup includes "Algorithms & Data Structures for Beginners" (25 hours) and "Advanced Algorithms" (25 hours), video lessons paired with interactive coding problems, Python-first. The famous NeetCode 150 problem roadmap and the associated YouTube walkthroughs are free; Pro runs $119/year or $297 lifetime as of August 2026.

Strengths: the free tier is genuinely generous, the problem curation is excellent, and the videos are short and to the point. If you already know your fundamentals and want to focus on interview prep, this is the tool for that job.

Weaknesses: it's teaching to the test (on purpose). You'll get very good at recognizing "this is a sliding window problem," but it's not as much of a deep dive into computer science theory and fundamentals as Boot.dev or some of the university courses.

ThePrimeagen's “The Last Algorithms Course You'll Need”

The Last Algorithms Course You'll Need is ThePrimeagen's 9-hour-20-minute workshop on Frontend Masters, which, fun 2026 fact, has rebranded to master.dev (their homepage announces "Today, Frontend Masters becomes Master.dev", and the signup pages already redirect). The course page has a "Watch Full Course for Free" button — you need a free account, while full platform access is $39/month.

Prime spent a decade at Netflix writing performance-critical software, and it shows: the course is fast, funny, and opinionated, covering search, sort, linked lists, trees, heaps, graphs, and LRU caches in TypeScript-flavored JavaScript. (He also teaches the Git and HTTP courses on Boot.dev.)

The limits: at 9 hours it's an in-depth marathon of a lecture, and while Prime is very hands-on as always, it's not an interactive learning platform like his Git and HTTP courses on Boot.dev, or the NeetCode platform. It's also a bit shorter than many others on this list (no dynamic programming, no shortest-path algorithms, no complexity theory). It's a workshop recording, so the "do the exercises" pressure is entirely on you. That said, Prime is the G.O.A.T. and you'll learn a lot from watching him crush algorithms in JavaScript.

Princeton's Algorithms, Part I: the best free course, with two big asterisks

Algorithms, Part I from Princeton's Robert Sedgewick and Kevin Wayne is one of the most decorated DSA courses on the internet: 4.9 stars from over 12,000 reviews, 1.46 million enrolled, and completely free. Sedgewick wrote the textbook... you may have seen the big red Algorithms book on a senior engineer's shelf.

The asterisks:

• There is no certificate. Princeton's policy, applied to both Part I and Part II. If you're taking a course partly to have something to show for it, this one produces nothing but knowledge. (Which, to be fair, is the part that gets you through an interview. I've written before about how certificates compare to degrees — the short version is that neither matters as much as demonstrated skill.)
• The assignments must be written in Java. If you're a Python or JavaScript person, you'll spend your first two weeks fighting the syntax instead of learning about stacks and queues.
• It is interactive, but not in the same way. The assignments are done on your local machine, and you upload files in a .zip to Coursera. It lacks all the convenience and feedback of a Boot.dev or NeetCode-style platform.

It's also genuinely academic in flavor: expect ~5 weeks at 10 hours a week for Part I alone, with a focus on the science of algorithms (analysis, proofs of correctness) more than interview patterns.

MIT 6.006: the actual MIT class, free

6.006 Introduction to Algorithms on MIT OpenCourseWare is exactly what MIT students take: full lecture videos from Erik Demaine and colleagues, lecture notes, recitations, problem sets with solutions, and real exams. Free, no signup, and no upsell anywhere.

Things to know before you commit:

• It assumes real prerequisites: MIT's intro Python course (6.0001) and discrete math (6.042J).
• The published version is from Spring 2020. Algorithms don't age quickly (Dijkstra's algorithm is from 1956... and it's still kicking), so this matters less than it would for, say, a React course.
• No certificate, no grading, no community. It's a pile of world-class materials. Nobody checks whether you did the problem sets, which can be a blessing or a curse depending on your self-discipline.
• It's lecture-first. The problem sets are excellent, but the default experience is watching a lecture. You have to supply the discipline to actually do the work.

6.006 is probably the most rigorous free option on this list. I cover it and the rest of the free university tier in more depth in our guide to learning computer science online.

UC San Diego's specialization

The Data Structures and Algorithms Specialization from UC San Diego is the biggest thing on this list: six courses, roughly 180 hours of estimated content, and Coursera suggests five months at 10 hours a week. It has 381,000 enrolled and a 4.6 rating from 16,750 reviews.

What I like: it's built around ~100 programming assignments (not just quizzes), it accepts solutions in C++, Java, Python and more, and the back half goes places most courses never do: 55 hours on graph algorithms, strings, advanced complexity, and a genuinely cool capstone where you assemble a genome.

The catches:

• Five months is a long time, and MOOC specialization completion rates are famously grim. Ask yourself whether you'll still be showing up in week 14.
• The certificate requires payment (or Coursera Plus); auditing is (maybe?) free... although I did encounter a paywall, not sure if that's due to me being enrolled in other Coursera courses or what. It's clearly not completely free and open in the purest sense.

If you want an academic path with a certificate at the end, this could be a fit.

GeeksforGeeks: wait, where did the DSA course go?

This one's odd enough that it deserves its own section. GeeksforGeeks' "DSA Self-Paced" course has been the default recommendation in Indian CS circles for years. But as of August 2026, the canonical course URL serves a completely different product: "Placement 360 – The Complete Tech Interview Program", a mega-bundle covering programming languages, DSA, OOP and low-level design, SQL, operating systems, aptitude tests, resume prep, and an "AI Toolkit."

It costs $139.98 in the US at the time of writing.

If you're targeting the Indian campus-placement pipeline, GfG's problem archive is an asset. However, I wasn't able to find a way to demo the content without paying, and it required a phone number to register for more information... so just based on that, this is my least favorite option on the list.

UC Berkeley Extension: $1,045 for 30 hours

Data Structures and Algorithms (COMPSCI X404.1) at UC Berkeley Extension costs $1,045 for 30 instructional hours. The Fall 2026 section runs live online, Thursday 6-9pm Pacific, September 10 through November 12. Demos are in Python; you can submit work in Python, Java, C, or C++.

To Berkeley's credit, they're transparent: price, schedule, and credit value are right on the page. And you get things self-paced courses can't offer: a live instructor, a fixed schedule, and most importantly 2 semester units of UC credit that can apply toward their software development certificate program.

That's roughly $35 per hour of instruction... and it's true that the same budget buys two full years of Boot.dev at $798 (54 hours of interactive DSA content plus ~48 other courses) with a couple hundred dollars left over, or almost nine years of NeetCode Pro, or Princeton's course for free. So, unless you specifically need university credits, or you know you only show up when a live class is on the calendar (a real and valid thing), the price-per-hour is pretty brutal.

Honorable mention: Udemy giants

No DSA roundup escapes Udemy, where Andrei Neagoie's "Master the Coding Interview: Data Structures + Algorithms" is the perennial bestseller.

The general Udemy caveat applies to the whole catalog (Colt Steele's JavaScript masterclass, Scott Barrett's Python course, Abdul Bari's C/C++ course): never pay list price (courses are routinely discounted by ~80%), and know that these are video courses where the exercises are optional and the temptation to watch at 2x and do nothing can be strong. At the time of writing the list price was $129.99, but with an 82% discount it was $22.99.

How to pick a data structures and algorithms course

DSA is a skill, like playing piano, and skills are built by doing reps (you've watched tutorials before and retained nothing... we all have). Princeton and MIT are brilliant lecture courses that work only if you religiously do the assignments. Boot.dev and NeetCode are built so that skipping the work isn't an option — the course is the work.

Whatever course you pick, the ratio of code-you-wrote to video-you-watched is the best predictor I know of for what you'll actually remember when you show up to an interview.

Interview prep and CS learning are different goals

"I want to pass the Google interview I have next week" and "I want to learn coding the right way" lead to different picks:

• Interview in weeks: NeetCode, or drilling the hands-on stuff from Prime's workshop. Drill patterns, do mock problems, and don't feel bad that it's teaching to the test.
• Fundamentals over months: Boot.dev's DSA courses, Princeton, MIT, or UCSD. Slower, deeper, and it compounds — it makes you better at your actual job, and builds an educational foundation for serious computer work.

Learn in the language you'll interview in

If you learn DSA in Java (Princeton) but interview in Python, you'll be translating under pressure, and on a time crunch you don't want any extra cognitive load. Python is probably the most common interview language — part of why Boot.dev, NeetCode, and MIT all use it. JavaScript is fine if you're interviewing for frontend or Node-first roles (Prime's course has you covered). Java and C++ still dominate certain enterprise and systems shops.