Resource Hub
3505 hand-picked resources for students, job seekers, career changers, founders, and AI learners — 100% free to browse with no account required.
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124 resources
RudderStack's free library of explainer articles on data engineering, data infrastructure and machine learning, covering topics such as generalization, deep learning and supplying customer data to LLM applications. RudderStack sells a customer data platform.
A free directory of recommended tech videos — talks, lectures, explainers, tutorials and documentaries — that can be filtered by type, length and upload date.
Learning app that uses AI to turn a chosen topic into short courses and quizzes. Its non-expiring free plan supports building and playing courses without a credit card; optional paid features are available.
The project page for a study finding that AI assistance reduces persistence and hurts independent performance once the tool is removed. Includes the paper and materials.
A self-directed, community-driven educational retreat for programmers in New York City, where participants work on projects of their choosing alongside other programmers.
Why I recommend it: The retreat is free to attend; participants cover their own living costs.
Free guides from Autoheal on site reliability engineering: alert triage, incident management, postmortem reports, MTTD vs MTTR, SLOs and AI-assisted reliability work.
Why I recommend it: Autoheal sells an AI reliability product; the guides are free to read.
Personal essay by engineer Dakota Fabro on mapping your own knowledge gaps — a practical reflection for people building technical careers.
A learning site aimed at helping non-technical people understand and use AI. The site blocked an automated check, so this description is based on the site name and focus; confirm details on the page.
AI study tool with guided lessons, visual explanations and homework help across school subjects. Has a free tier; a paid Plus plan unlocks more usage.
LinkedIn help page on getting LinkedIn Learning through your public library card.
Why I recommend it: LinkedIn Learning is normally paid; this route is free only if your library offers it.
Free video shows made by and for developers, including series like The Build Log and The Full Stack, where founders and teams build real products on camera.
Why I recommend it: Free to watch. Episodes are sponsored, so treat them as behind-the-scenes stories rather than neutral reviews, and check whether the tooling fits your own stack before following along.
Free reading app from OverDrive that borrows ebooks, audiobooks and magazines from your local public library with a library card. Works in a browser or on iOS, Android, Kobo and Kindle (US libraries only), with offline downloads, CarPlay and Android Auto support, holds, and tagged reading lists.
Why I recommend it: This is how you read the paid books on this site without buying them — most business, career and technology titles are in public library collections. What you need is a library card, which is free where you live. The catch is availability, not price: your library chooses what it licenses and popular titles come with waiting lists, so place holds early rather than expecting a book on the day you want it.
The full report of MIT's Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training, published 13 August 2026 after five months of meetings and outreach. The committee — students, faculty from every school, and staff from the MIT Libraries and Teaching and Learning Lab — was charged with assessing current AI use, identifying teaching and assessment innovations, and proposing an AI use policy. It sets out eight guiding principles (be humble, be bold, put humanity front and centre, lean into learning, teach with intentionality, no one size fits all, augmentation not automation, think beyond the classroom) and three groups of recommendations. Free to read online and free to download, with appendices and an FAQ.
Why I recommend it: The most useful part is the principles section — 'augmentation not automation' and 'teach with intentionality' are phrases you can borrow directly when you have to argue an AI policy to a school, a manager or a client. Be straight about what it is, though: MIT examining MIT, written for a residential research university, so its recommendations do not transfer unchanged to a community college, a bootcamp or a workplace.
Turns books and documents into scrollable, bite-sized learning cards with AI summaries and quizzes.
From the site: What is AI smart scrolling? ScrollEd pioneered AI smart-scrolling technology that transforms books into scrollable, bite-sized learning cards with AI summaries and quizzes. Learn faster in 5-minute sessions.
Why I recommend it: The free tier is limited: demo content only, no file uploads, and ads. Pro is $6.99 a month (currently offered free for three months to early members), so treat the free plan as a look around rather than a usable reading tool.
Well-explained computer science and programming tutorials, quizzes, and interview practice problems.
From the site: Your All-in-One Learning Portal. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
Why I recommend it: Ad-supported; most articles and practice problems are free to read.
A curated set of free learning material for legal professionals who want to understand data and AI: primers, courses, tools and reading, gathered in one place.
From the site: Learning Legal Data Science: An Introductory Course on Legal Data Science in R. https://www.youtube.com/embed/iOLLbiW9OPsThe best way to understand what computer science and artificial intelligence can and cannot do in the legal domain is to learn how to program yourself. Acquiring these skills allows you to harness t…
Why I recommend it: A strong starting point if you are in law and feel behind on data and AI. The links are free; some point to external courses that have their own paid upgrades.
A reading layer over Wikipedia: cleaner article pages, hover previews, timelines, and a chat that answers only from the Wikipedia article you are reading and the articles it links to, with every answer linked back to its source.
Why I recommend it: Useful precisely because it refuses to answer from anywhere but Wikipedia — you can check every claim. Still Wikipedia underneath, so treat it as a starting point, not a citation.
Free, well-written documentation and tutorials for building and hosting sites, APIs and AI workers — one of the better free places to learn modern web infrastructure.
From the site: Connect, protect, and build everywhere.
Why I recommend it: Free docs with working examples. A good self-teaching path if you want infrastructure skills on your resume.
A free newsletter explaining ideas in AI in plain English — mostly what and why, a little how.
From the site: Ideas in AI, preferably in English. Mostly what and why, a little how. Click to read Very Sane AI Newsletter, by SE Gyges, a Substack publication with thousands of subscribers.
Why I recommend it: A good weekly read if you want to understand AI without the hype or the math.
A free explorer for new arXiv research with plain-language paper summaries, topic pages and video overviews, so you can follow AI research without reading raw papers.
From the site: Your first stop to discover and learn about new arXiv research. Detailed paper summaries, video overviews, and more — no prompting required.
Why I recommend it: The fastest way I know to keep up with AI research when you are not a researcher. Free to browse.
A free ebook walking through reinforcement learning from the basics to RLHF, written for practitioners rather than researchers.
From the site: Reinforcement learning (RL) is transforming how reliable AI agents are trained and deployed. Discover real-world use cases, efficiency techniques like LoRA, and practical patterns you can apply today.
Why I recommend it: Free download in exchange for an email address. Solid grounding if you keep seeing "RLHF" and nodding along.
The standard free Python distribution for data and AI work — package management, notebooks and thousands of libraries in one install.
From the site: Anaconda is the trusted foundation for AI-native development. Secure, orchestrate, and accelerate data and AI at scale, from first experiment to production.
Why I recommend it: Free for individual use. If you are learning Python for data work, this saves you a week of setup pain.
Shane Parrish's long-form interviews on decision making, judgement and learning, with free episodes and transcripts.
Why I recommend it: Useful on a commute when you're weighing a career decision and want better questions rather than quick answers.
Eliezer Yudkowsky's free novel-length story teaching scientific reasoning, cognitive bias and decision-making through fiction; widely read as an entry point to rationality writing.
Why I recommend it: An unusual entry, but it is free and it teaches how to test your own reasoning better than most textbooks.
