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Foundations

Twenty-two modules form the common technical core. The ordering is opinionated; the pages are also usable independently as references.

# Module Prerequisites Exit capability
1 Mathematical reasoning + proof None beyond algebra Own definitions, quantifiers, implication, counterexample, induction, proof structure.
2 Calculus + vector calculus Algebra/trigonometry + Module 1 Own limits, derivatives as local linearization, integrals as accumulation, gradients/Jacobians, line/surface integrals and field theorems.
3 Linear algebra Modules 1-2 can overlap Own vector spaces, projections, least squares, matrix maps, rank/nullspace, conditioning, SVD/eigenstructure.
4 ODEs + dynamical systems Modules 2-3 Translate changing systems into state equations; solve/analyze equilibria, stability, oscillation, nonlinear behavior and feedback.
5 Probability Modules 1-3 Quantify uncertainty, conditioning, expectation, dependence, transformations, concentration and asymptotics.
6 Statistics + causal inference Module 5; basic linear algebra Define estimands; separate prediction from intervention; identify confounding/selection/measurement bias; estimate and stress-test effects.
7 Scientific computing Modules 2-5 Know conditioning, numerical stability, approximation, iterative solution, ODE/PDE discretization and computational verification.
8 Optimization Modules 2-3, 5, 7 Formulate objectives/constraints; understand convexity, duality, KKT conditions and numerical optimization; audit objectives.
9 Information + signals Modules 3, 5, 7 Own entropy, mutual information, channel capacity, transforms, sampling, filtering, spectral reasoning and estimation limits.
10 Control + estimation Modules 3-5, 7-9 Design closed loops; analyze stability/robustness; infer hidden state; reason about controllability, observability and tradeoffs.
11 Metrology + experiments Module 5; runs in parallel from Week 1 Calibrate, quantify uncertainty, design informative experiments, distinguish process variation from measurement variation, reproduce results.
12 Mechanics + electromagnetism Wave 1 calculus, vector calculus, ODEs, linear algebra Convert forces, fields and conservation laws into predictive models; move between particle, rigid-body, orbital and field descriptions.
13 Thermodynamics + statistical mechanics Wave 1 probability, calculus, ODEs Track energy/entropy/free energy; derive equilibrium tendencies; connect microscopic states to macroscopic limits and transport.
14 Quantum + condensed matter Wave 1 linear algebra, ODEs, probability; Module 1 Reason with wavefunctions/operators and connect quantum states to bands, semiconductors, phonons, magnetism and superconductivity.
15 Chemistry + materials Modules 1-3; Wave 1 thermo/optimization concepts Predict bonding, reaction direction/rate, electrochemistry, diffusion, phase behavior and processing-structure-property links.
16 Electronics + embedded systems Module 1; Wave 1 signals/control Design and instrument circuits from passive networks through semiconductor interfaces, sensing, power conversion and real-time embedded control.
17 Mechanical design + fluids + structures Module 1; Module 4; Wave 1 control/optimization Turn loads and flows into safe geometry; reason about stress, fatigue, shells, fluids, pumps, pressure systems and mass-efficient structures.
18 Molecular + cell biology Module 2; Module 4; Wave 1 dynamics/probability Model cells as chemical, energetic, informational and mechanical systems; understand membranes, metabolism, signaling, division and gene expression.
19 Genetics + evolution + systems biology Module 7; Wave 1 dynamics/probability/causal inference Reason about inheritance, variation, population change, gene circuits, network motifs, stochastic expression and evolutionary robustness.
20 Neuroscience + physiology Modules 5,7; Wave 1 signals/control/probability Connect electrophysiology and neural coding to whole-body homeostasis, cardiovascular/respiratory/endocrine/renal control.
21 Manufacturing + operations Modules 4-6; Wave 1 optimization/metrology Translate prototypes into processes with rate, yield, variation, quality, cost, maintenance, supply chain and learning curves.
22 Safety + reliability + security All prior modules; Wave 1 causal/metrology/control Design systems that remain safe and dependable under component failure, software defects, organizational drift, misuse and adversaries.

Visual dependency map ->

Two layers

  • Foundations I: representation, inference, computation, dynamics, optimization, information, control, measurement.
  • Foundations II: physical, biological, industrial, and safety substrates.