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Pricing & Plans

Yes — the Foundation track (Python, SQL, Pandas, Statistics, Git, Intro ML) is completely free. No credit card required.To access your chosen career track (AI Engineer, Data Scientist, ML Engineer, or Data Engineer), you’ll need a Pro plan.
  • Pro Monthly — $29/month
  • Pro Annual — $199/year (~43% saving vs monthly)
Both plans include full access to all four career tracks, unlimited labs, AI tutor, cohort matching, and the full gamification system.
Yes. Cancel from your account settings at any time. You keep access until the end of your current billing period.

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Learning & Content

Foundation takes approximately 7 weeks. Each career track takes 20–22 weeks after Foundation. That’s based on ~1 hour of learning per day.Most learners finish faster or slower depending on their background and pace.
Foundation is designed for learners with basic programming knowledge — you should be comfortable writing a Python function and understand what a variable is. You don’t need prior data science or ML experience.Career tracks assume Foundation is complete.
Labs are reviewed by the AI Code Review agent, which gives structured feedback across correctness, code style, and efficiency. It’s not a simple pass/fail — you get detailed inline comments and follow-up questions to deepen your understanding.There is no grade. The goal is iteration and mastery, not a score.
Your streak resets if you miss a day. Use a Focus Freeze (earned by completing modules) to protect your streak for one day.You can also enable Weekend Rest Mode in settings to exclude weekends from your streak calculation.
Skills decay at 2% per day if you don’t revisit them. This mirrors the real forgetting curve and keeps your skill graph honest. The spaced repetition system will notify you before important skills drop too low.

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Cohorts

The matching algorithm runs every Sunday at midnight UTC. Once you have enough skill mastery data (typically after 2–3 weeks on the platform), you’ll be included in the next matching run and notified when your cohort is ready.
Each cohort has a weekly health score based on standup posts, peer reviews completed, and challenge submissions. If your cohort’s health drops below 40, admins will check in.If you’re inactive for an extended period, you may be removed from your cohort and re-matched when you return.
Yes. When you submit a lab, you’re assigned a cohort peer to review it. Your peer has 48 hours to give feedback. You earn XP for completing reviews — and your cohort’s health score depends on review completion.

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Technical

No. The Monaco code editor runs entirely in your browser. All labs execute in a sandboxed environment — no local setup required.
Safua works on any modern browser: Chrome, Firefox, Safari, and Edge. We recommend Chrome for the best Monaco editor experience.
Not yet. The platform is optimised for desktop. Reading lessons work well on mobile, but labs require a larger screen for the best experience. Mobile apps are on the roadmap.