Arqam

أرقم

From first steps to real work in AI and data.

One connected journey to AI-native AI engineer, data scientist or AI researcher. Built only from free, openly licensed material, and turned into active learning by a tutor that cites its sources.

Private alpha: January 2027 Try the preview Follow the build
The Arqam mark: a house with three rising bars and a point of light
Today screen on a phone: next steps with their sources, journey progress and new papers
Today: what to do next, and why.
Study space on desktop: a video with chapters, a licence note, and the tutor al-Murshid answering with citations
A study space: your sources on the left, al-Murshid on the right, every answer cited. Design mockups; try the running preview.

How it works

One journey, one record of progress. Everything you watch, read, review and build moves the same map forward, so "where am I, and what next?" always has an answer.

01 · Choose

A track

AI-native AI Engineer, Data Scientist or AI Researcher: learn the fundamentals, do the work with AI, verify the result. A short placement quiz skips what you already know.

02 · Study

In a space

Videos, course text, repos and papers side by side with al-Murshid, who answers only from your sources.

03 · Practise

Cards and quizzes

Flashcards with spaced repetition and quizzes, generated from the sources and cited, accepted by you.

04 · Grow

Skill by skill

Mastery per skill, milestones, streaks and new arXiv papers for what you are learning now.

Only material you are free to use

Arqam links and embeds anything publicly available, and only builds summaries, cards and quizzes from material whose licence allows it: CC BY, CC BY-SA, CC0, MIT, Apache and similar. Every item shows its licence, and every generated card shows where it came from.

  • freeCodeCamp
  • Hugging Face Learn
  • Dive into Deep Learning
  • arXiv
  • GitHub
  • YouTube (embedded)
  • OpenStax
  • Distill
Journey screen: seven milestones with skills and mastery Review screen: a flashcard about attention with its cited source and four grading buttons Onboarding screen: choose a track and your time per week

When

  1. NowEarly preview at arqam-stg.siralabs.org, rebuilt as the work lands. Data there may be reset.
  2. Oct – Dec 2026Foundation, the connected learning model, licensed content, the study engine.
  3. January 2027Private alpha with invited learners on three tracks.
  4. Jan – Feb 2027arXiv papers, sharing, cohorts and public journey templates.
  5. March 2027Public beta with Free and Pro plans. Bring your own AI key on Free.

Dates are the current plan and may move. Arqam is part of Sira Labs.