A scholarly guide, honestly written.
AlgoMastery is a free, independently-written curriculum on data structures and algorithms. It exists because the internet is full of "ten tricks to ace your interview" — and almost empty of the slower, more faithful treatment the subject deserves.
The mission
Most algorithm content online exists for two reasons: to sell a course, or to rank for interview keywords. Neither produces the kind of long-form explanation that actually teaches the subject. AlgoMastery is an attempt at the opposite — nine modules on the canon of data structures and algorithms, written like a graduate-school textbook but priced like a public library: free, forever, no login, no paywall.
The animating belief is that the subject is beautiful. A correctly-explained hash map is more memorable than a mnemonic. A well-chosen metaphor for recursion does more work than a dozen practice problems. The craft of explanation is itself worth preserving, and most of the internet has abandoned it for format tricks and video thumbnails. This site is an attempt to make the long-form essay respectable again, in one narrow domain.
The author
AlgoMastery is written and maintained by the site's founder — a software engineer with a background in computer science and years of production experience across data infrastructure, compilers, and developer tools. The pedagogical stance is first-hand: every concept on this site has been used to ship code, debug production incidents, pass and give technical interviews, or teach a colleague. Content is written from practised understanding rather than paraphrased from Wikipedia.
The site is small, careful, and slow-moving by design. Every module goes through several drafts before publication. When an explanation fails to land, it's rewritten from scratch rather than patched. The goal is that the curriculum reads like a single voice arguing consistently, not a pile of stitched-together articles.
The pedagogy
Three commitments shape every piece on the site:
- Worked examples, always. Every algorithm is accompanied by at least one concrete, traceable input and a step-by-step walkthrough. An algorithm you cannot trace on paper is an algorithm you do not understand.
- Complexity with reasoning. "Time: O(n log n)" is a claim, not an explanation. Every complexity statement on this site is accompanied by the argument for why — the counting of operations, the amortisation, the proof of the lower bound.
- Common mistakes, named. Every module ends with a "where beginners go wrong" section. These are not hypothetical mistakes — they are the mistakes actually made in interviews and pull requests, recorded as they appear and explained at the point of failure.
What you won't find here
- Video content. Text beats video for technical material that must be re-read, scanned, and searched.
- Tracking beyond what's needed for the site to function. See the privacy policy.
- "Ten tricks" listicles. Ten tricks without the underlying model are ten things to forget.
- Paywalls, courses, or upsell CTAs. The content is the product, not a lead magnet for something else.
- User accounts or gamification. Anonymity is preferred; your reading patterns are none of our business.
How the site stays free
AlgoMastery is supported by carefully-placed display advertising — only in non-reading positions (between modules, in the footer, on the topic index). No advertising appears within prose or in the middle of code blocks. The reading experience is the contract; ads live in the margins or they don't live at all. If a future advertiser's policy conflicts with that, we change advertisers.
There is no affiliate linking. There is no sponsored content. There is no newsletter-driven course funnel. If the economics change, the change will be announced here first.
What's coming
The current nine modules are the foundation — the topics a working engineer should know cold. The planned next phase is a set of long-form essays organised around classic texts in the field, walking modern readers through the most useful chapters of books like The Algorithm Design Manual, Introduction to Algorithms, and Competitive Programmer's Handbook. The same pedagogy applies — worked examples, reasoning, named mistakes — but the scope extends to topics that don't fit neatly into a standalone module.
Contact & corrections
Algorithm content is subject to subtle errors — an off-by-one in a code sample, a misstated complexity, a missed edge case. Corrections are always welcome and are acknowledged at the bottom of the affected page. Use the contact page or email hello@algomastery.dev directly.