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Coursetexts – Open-Access Graduate Course Library (Manifund Project Page)

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Coursetexts is an open-access library publishing graduate-level course notes from Harvard and MIT, aiming to democratize advanced education. While not directly AI safety focused, it supports open knowledge infrastructure that could benefit AI safety researchers and students seeking frontier technical education.

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Importance: 12/100othereducational

Summary

Coursetexts is a nonprofit initiative publishing open-source course notes for Harvard and MIT graduate-level classes with professors' consent. The project aims to make advanced education freely accessible, targeting 50 courses by August 2025. Funding via Manifund supports automation, copyright handling, and contractor review work.

Key Points

  • Open-sources graduate-level course notes from Harvard/MIT with explicit professor consent, currently 20 courses available.
  • Goal of 50 courses by August 2025 at ~$400/course cost, with automation to reduce unit costs.
  • Advised by Lawrence Lessig, Peter Suber, and Michael Nielsen — prominent open-access and open-science advocates.
  • Team includes MIT graduates with experience in open-source education and AI research pipelines.
  • Raises funds via Manifund crowdfunding; previously received $10K from The Institute and Michael Nielsen.

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Coursetexts

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Project summary

Coursetexts is a library of advanced course material. We’re publishing course notes for Harvard’s graduate-level classes as those courses are being taught. All our courses are open sourced with the professor’s explicit consent.

We grew up teaching ourselves online. When school didn’t satisfy us, we turned to the Internet: computer science papers, physics textbooks, and essays galore. But our reading often hit a wall; not from lack of curiosity, but lack of access. Paywalls or out-of-date material limited what we could learn. We have high hopes for Coursetexts. We want it to curate the highest quality education on the planet so anyone can be a true expert in their desired field. And, we want it to serve as a guide to frontier research as its being published.

We’re building the library we wish we had — and we’re excited for the next generation of learners to do more than we could have imagined. You can see our existing courses at coursetexts.org.

What are this project's goals? How will you achieve them?

Overall, we want to open source as many new, advanced courses as possible for as low of a unit cost per course. Our concrete goal is 50 by August 2025. Right now, we have 20 up and it costs ~$400/course between AI compute to clean up the videos, and to pay contractors to edit and review the courses. We believe we can drive this down via automation.

How will this funding be used?

Money will go to both engineering work to automate the most expensive processes, build copyright handling pipelines with AI to attribute and replace copyrighted material, and pay contractors for their time to review course info manually.

Who is on your team? What's your track record on similar projects?

Selena; MIT grad who founded Momentum AI, a 501c3 that helped 1000+ underresourced high schoolers to ship projects in ML research and web development.

Aayush; MIT graduate who previously co-started and currently advises MIT SOUL on open-sourcing the MIT economics curriculum. Brings experience in building organizations and AI processing pipelines, with direct knowledge from work

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