Course
Mathematics for Machine Intelligence
Rebuild linear algebra, optimization, and probability muscles that underpin AI systems.
Level
Intermediate
Duration
60 hrs
License
CC-BY-SA
Provider
PowerProgress x MIT OCW
AI tutor ready
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Readiness status
100%
170/12 manifest entries logged
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Civic missions bottleneck
3 weekly posts - 50 live missions. Close the 48pt gap by running the recommended playbook.
Readiness
52%
Gap to 100%
-48 pts
Target
120 weekly updates / 30 missions
Live impact
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Module
Vector Systems & Stability
Translate linear algebra identities directly into embedding and attention code paths.
1 lessons · 2 takeaways
Mission outcomes
- Explain how basis changes impact representation learning.
- Show matrix calculus steps for gradients and low-rank adapters.
Module
Probabilistic Signals
Size evaluation runs and calibrate models using practical probability tools.
1 lessons · 2 takeaways
Mission outcomes
- Compute bounds for accuracy, latency, and safety metrics before deployment.
- Draft calibration rituals that tie math to day-2 operations.