RS Track · PhD-Level AI / ML / GenAI
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Self-directed doctoral program · progress saved in this browser

Research-scientist depth in AI, ML & generative models.

Seven-phase core spine plus optional specialization tracks. Every item is checkable with a working link. Major learning units expand to show rationale, prerequisites, key topics, mastery checks and a required artifact — and support four states so you can mark real mastery, not just "watched it." Beyond that, major units now track six independent competency dimensions (Understand → Derive → Implement → Experiment → Critique → Research) that you back with evidence records, not just self-rating — because completing a course is not the same as being research-ready. Specialization tracks and modules start collapsed to keep the page clean; open what you're working on. Mark each specialization track's role — Primary / Secondary / Reading literacy / Not pursuing — from its section header; the Research, Dashboard and Gates tabs above turn that plus your evidence into a hypothesis log, a decomposed progress dashboard, and five defended research checkpoints.

Not started In progress Done Mastered · click a row to cycle · major units cycle all four states
Self-assessed Evidence-backed Externally validated · competency dimensions are labeled by how well-supported they are
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Research

The apparatus that turns study into contribution.

Recurring research activity, logged explicitly — and a running Observation → Question → Hypothesis → Experiment → Result log. Nothing here is inferred from ticking a paper "done."

Dashboard

Decomposed progress — never one misleading percentage.

Resource completion, competency development, evidence strength and research independence are tracked and shown separately, on purpose.

Gates

Research gates — defended, not checked off.

Five explicit checkpoints. Each supports a real status (not attempted / self-assessed pass / external pass / needs revision), notes, and evidence links.

Frontier

Live research fronts.

A research radar you maintain yourself — topics, why they matter, key papers, and when you last reviewed each one — plus the Frontier module from the curriculum below it. The radar highlights topics due for review on a rolling basis; it never assumes a particular current year.