The Last Algorithms Course You'll Need vs Web Performance Fundamentals, v2

Across roughly nine hours and 60 lessons the course covers Big O time and space complexity, arrays, linked lists, queues and stacks, a ring buffer, recursion, the classic searches and sorts (linear, binary, bubble, quick), trees with BFS and DFS, heaps, maps, graphs with adjacency lists and matrices, and Dijkstra's shortest path. Reviewers repeatedly call it content-dense and "not the typical watered down content you find often on online courses." The honest mark-down is that it is implementation-first and fast — it condenses a full-semester CS course into under ten hours, so it favours breadth and live coding over slow, proof-heavy depth.

ThePrimeagen is the reason this course is so widely recommended. Reviewers describe his explanations as "full of joy and charisma," call him "an excellent communicator" who is "both down-to-earth and incredibly skilled and intelligent," and note that "you won't get bored and fall asleep." He implements most algorithms live rather than showing finished code, which learners consistently single out as the high point. This is one of the most engaging instructors in the DSA space and it shows in the 4.9/5 rating.

The course is completely free — all you need is a free Frontend Masters account — yet it sits behind, and is the same quality as, Frontend Masters' paid catalogue. For roughly nine hours of well-produced video plus a bespoke practice tool, reviewers call it "a worthy investment" and say "there is no other algorithm course that can teach you so many topics in such an efficient way." The only caveat on value is the subscription framing: the deeper Part 2 (advanced algorithms) sits behind a paid Frontend Masters subscription.

The standout practical feature is the kata-machine, a bespoke GitHub repository ThePrimeagen wrote that generates a fresh daily set of algorithm exercises with a ready testing environment, so you implement each structure from scratch in TypeScript rather than just watching. Learners praise this as the thing that makes the knowledge stick. The caveat is that there is no graded capstone or certificate, and some implementations (notably the doubly linked list) are "complicated, or rather convoluted, to implement," which can stall practice.

The stated goal is to teach enough DSA that, after practice, you could pass interviews at a large tech company, and reviewers report it delivered exactly that mental model — one four-year professional said "this was exactly what I needed to get back on track." The patterns (Big O reasoning, BFS/DFS, Dijkstra, the common sorts) are the bread and butter of coding interviews. But it is a foundation, not a credential: there is no certificate, and complete beginners will need significant outside practice before the interview goal is realistic.

The course covers the full stack of modern web performance knowledge in approximately six hours — a tight, well-curated curriculum that avoids the padding common in longer Udemy-style recordings. It opens with the psychology of perceived performance (drawing on David Maister's "Psychology of Waiting Lines"), then moves through Core Web Vitals metrics (LCP, CLS, and INP, which replaced FID as an official Google signal in March 2024), measurement APIs, synthetic testing with Lighthouse and WebPageTest, Real User Monitoring with CrUX, and finally concrete optimization tactics for each metric — TTFB, FCP, LCP, layout shift prevention, and interaction latency. The October 2024 update brought the curriculum fully current with the INP transition, so learners are not working with obsolete tooling or metrics. What sets the content apart from generic performance tutorials is its insistence on real user data before optimization. The recurring lesson — "focus on your worst metric, fix the most basic thing first, and confirm with RUM" — is a workflow, not just a collection of tips. The course also links performance work directly to business outcomes: conversion rate, SEO rankings, and user retention statistics are woven into the justification throughout, which gives engineers the language they need to advocate for performance work with non-technical stakeholders. The GitHub workshop repository (113 stars, 87 forks as of mid-2026) demonstrates the exercises have genuine uptake in the developer community.

Todd Gardner is one of the most credentialed practitioners teaching web performance in any format. As co-founder of TrackJS and Request Metrics, he has spent years building commercial RUM tools and working directly with thousands of development teams on performance problems — a background that produces very different teaching than a course built purely from documentation. His Frontend Masters blog articles (published November 2024 on INP and February 2025 on image optimization) extend the same practical, measurement-first methodology into the broader developer community. Student feedback collected from the official course page is unusually consistent in citing his teaching clarity as a differentiator. Anurag Bhandari wrote "Wonderfully planned and executed. Such a heavy topic explained in such simple terms." Pedro Antônio Pereira called it "a masterclass in how to understand web performance." Ryan Davidson, recommending it broadly, wrote: "Great blend of breadth and depth in the performance space. All web engineers — backend or frontend, junior or senior — should be taking this course!" The breadth of that recommendation — extending to backend engineers — reflects how Gardner anchors the course in concepts (HTTP caching, server response times, rendering pipelines) that apply regardless of whether you write CSS or database queries.

The course is included in a Frontend Masters subscription, priced at approximately $39/month or $390/year (annual plans have carried a 17-20% discount in 2025-2026). A seven-day free trial is available. For a subscriber who accesses even two or three courses, the per-course cost is minimal, and the Web Performance Fundamentals course is among the most immediately actionable in the entire library — the techniques taught apply to any existing project without needing to rebuild or refactor an architecture. Deeptiman Mallick's testimonial captures the evergreen value: "This course is like a bookmark to come back to when we're working on performance." Unlike courses that you complete once and set aside, the performance metrics and tools taught here — Lighthouse, WebPageTest, CrUX — are ones practitioners return to on every new project or optimization sprint. The value proposition is strongest for working developers with a real codebase to optimize; the course is less compelling as a purely theoretical exercise for learners with no project to apply it to. There is no standalone purchase option, so non-subscribers must commit to at least one month of the full subscription.

The hands-on component uses a real Node.js + Express e-commerce project — "Developer Stickers Online" — which is deployed to multiple regions and available on a global CDN with HTTP/3 support, making it possible to test real network conditions rather than synthetic localhost scenarios. Students work with actual Lighthouse scores, WebPageTest waterfalls, and CrUX field data rather than simulated metrics, which bridges the gap between tutorial and professional practice. The workshop's focus on a single, realistic project (rather than a series of disconnected toy exercises) is appropriate for the subject: web performance work lives in real measurement data, and the course correctly models that. The project repository's 87 forks suggest learners actively run the exercises rather than just watching. The main limitation is scope: the project is a static storefront, so learners working primarily on Single Page Applications, server-rendered frameworks like Next.js, or complex state-heavy UIs will need to extrapolate some of the tactics. There is no separate project tier with more complex application types.

Web performance is one of the highest-ROI skills a working web developer can acquire in 2024-2026: Core Web Vitals are a confirmed Google Search ranking signal, and the business case studies cited throughout the course (eCommerce and SaaS conversion improvements correlated with performance gains) are drawn from real production data. Gardner's background running RUM tools for thousands of teams means the tactics are not academic — they are the same ones practitioners reach for when a client's LCP score drops. Multiple student reviews specifically noted immediate applicability: Álex Castelo wrote that the course made them realize "how easy it can be to boost a website's performance exponentially," and Yuganshu Mohan distilled the practical lesson as "focus on the worst metric and perform the most basic fixes." The methodological frame — measure with real user data first, then fix, then confirm — transfers directly to professional performance audits. Taran Bains, writing an extended reference post from the course material in August 2025, used it as the foundation for a comprehensive web performance guide, which is a reliable signal that the content holds up as a reference long after the initial watch-through.