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Curriculum overview

Mag.AI-S (Magister of Artificial Intelligence in Science) is 18 courses in three terms. You progress from world models, measurement, and reproducibility to experiments, inference, and literature-scale systems, then to competition, allocation, governance, and a capstone thesis. Work is artifact-driven: you build executable articles (Jupyter notebooks in each course’s Jupyter Book, run in iNQspace), not slide-only summaries. Policy: Executable articles.

Each course is published as its own book (separate site). The table below links to those books; the full index is on Course sites.


Program arc

TermThemeWhat you’re building toward
I — World models & integrityHypotheses, uncertainty, reproducibility, and ethics as executable systemsWorlds you can test before you scale claims
II — Evidence & systems at scaleExperiments, statistical learning, simulation, literature intelligence, instrumentsCoordinated pipelines with delays, noise, and honest failure modes
III — Strategic scienceComparison, policy, allocation, autonomy, and governanceStrategic depth, governed autonomy, and a defense-ready thesis

Typical path: complete Term I (AINS-S6001 → AINS-S6006), then Term II (AINS-S6101 → AINS-S6106), then Term III (AINS-S6201 → AINS-S6206). Entry: AINS-S6001 is the recommended start.

Technical spine: Across all terms, the program weaves in AI literacy (evaluation, grounding, retrieval, generative workflows, scoped tooling). See the full curriculum under AI literacy spine.


Term I — World models & integrity

CodeCourseCore focus
AINS-S6001Scientific World Models & Executable HypothesesAssumptions, observables, and tests as the smallest honest world
AINS-S6002Measurement, Uncertainty & CalibrationError, calibration, and limits as first-class objects
AINS-S6003Computational Reproducibility & ProvenanceEnvironments, seeds, and lineage that survive reruns
AINS-S6004Data Systems, Documentation & LineageSchemas, metadata, and audit trails
AINS-S6005Literate Computation & Experiment LogsNotebooks and logs as inspectable science
AINS-S6006Ethics, Integrity & Responsible ConductIntegrity, authorship, and misuse boundaries

Term II — Evidence & systems at scale

CodeCourseCore focus
AINS-S6101Experiment Design & Causal ReasoningDesign and identification for strong claims
AINS-S6102Statistical Learning & Model EvaluationGeneralization, evaluation, and honest metrics
AINS-S6103Simulation, Generative Models & Synthetic DataSynthetic data and simulators under constraints
AINS-S6104Literature Intelligence, RAG & Evidence SynthesisRetrieval, grounding, and synthesis at scale
AINS-S6105Instruments, Signals & ML for MeasurementSignals from instruments and learned measurement
AINS-S6106Open Science, Collaboration & Review Stress TestsAdversarial review and collaboration fragility

Term III — Strategic science

CodeCourseCore focus
AINS-S6201Competing Hypotheses & Model ComparisonModel comparison and strategic interaction
AINS-S6202Research Strategy as Policy Under UncertaintyPolicy mapping states to actions
AINS-S6203Portfolio & Resource Allocation for Research ProgramsBudget and risk across initiatives
AINS-S6204Autonomous Lab & Instrumentation SystemsAutonomy with human-in-the-loop boundaries
AINS-S6205Safety, Governance & Control in Scientific AIGovernance and oversight for scientific AI
AINS-S6206Magisterium Thesis (Science)Capstone — deploy, validate, document, defend

Where to go next


The Castalia Institute Magisterium confers proprietary credentials based on demonstrated work and evaluation. These credentials are not accredited academic degrees and do not confer professional licensure.