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How Cars Work — and How Mechanics Do Their Jobs: the four-stroke cycle, engine anatomy, the air path, fuel and injection, ignition and knock, engine management and closed-loop control, cooling and lubrication, emissions aftertreatment, diesel specifics, transmissions, driveline and differentials, suspension, steering and alignment, brakes, tyres, the 12V system, vehicle networks, ADAS, air conditioning, EV architecture, batteries and degradation, high-voltage safety, hybrids, corrosion, diagnostic method, OBD-II and scan data, tools, common misdiagnoses, and maintenance and shop economics.

eCommerce Development: commerce and payments systems — architecture, the payment lifecycle (authorization, capture, settlement, refunds), integration engineering (idempotency, webhooks, reconciliation, state machines), PSPs and gateways (Stripe, PayPal, Adyen, Braintree), payment methods and rails (cards, wallets, ACH/SEPA, SWIFT/ISO 20022, BNPL, instant payments), SCA and 3-D Secure, authorization rates and decline handling, fraud and chargebacks, PCI DSS scope and the SAQ A trap, subscriptions and billing, marketplaces and payouts, tax and cross-border, the platform layer (Shopify, headless, custom), catalog/cart/checkout and conversion, and agentic commerce protocols.

Geoscience: Earth structure and plate tectonics, minerals and rocks, deep time and stratigraphy, deformation and structure, earthquakes and seismology including the magnitude-versus-intensity distinction and prediction versus forecasting, volcanism, surface processes, soils, surface hydrology, groundwater, oceanography, the cryosphere, biogeochemical cycles, resources, natural hazards, and observation and geophysics.

Game Theory: the framework and what rationality actually assumes, normal and extensive form representations, dominance, Nash equilibrium and what it is not, the classic games, zero-sum and minimax, sequential games and subgame perfection, repeated games and the folk theorem, incomplete information and Bayesian games, bargaining, cooperative game theory, mechanism design and auctions, matching markets, evolutionary game theory, where the theory fails empirically, and computational game theory.

UI/UX Design Principles: the perceptual and cognitive science underneath interface decisions, usability heuristics and mental models, information architecture and navigation, input and interaction per form factor, layout and responsive/adaptive design, visual design (typography, color, space, motion, iconography), design systems and tokens, platform conventions (Apple HIG, Material 3, GNOME/KDE HIG, Fluent), accessibility law and practice (WCAG 2.2/3.0, EAA, ADA Title II, APCA), UX writing, forms/onboarding/conversion, research and evaluation, ethics and dark-pattern regulation, and AI-era interface patterns.

Cooking, Cleaning and Waste Sciences: the food science (heat transfer, proteins and meat, browning, starch, gluten and gels, fats and emulsions, salt and brining, acid and pH, flavour, fermentation, baking and leavening), food safety (pathogens and temperature, HACCP, cross-contamination and allergens), food service (kitchen organization, restaurant economics, menu engineering, regulation and inspection), cleaning chemistry (surfactants and soil types, water hardness, the cleaning-sanitizing-disinfecting distinction and the mixing dangers, laundry), and waste (wastewater treatment, the waste hierarchy, landfills, recycling assessed honestly, composting).

Electromagnetism and the Physics of Electricity: the abstraction ladder, charge and Coulomb's law, fields and Gauss's law, potential and capacitance, dielectrics, what current actually is, resistance and Ohm's law, where the energy actually flows, circuit theory and its validity limits, AC and impedance, power, RMS and power factor, magnetic fields, induction, inductance and transformers, magnetic materials, Maxwell's equations, electromagnetic waves, transmission lines, magnetism as relativistic electrostatics, conduction and band theory, semiconductors, superconductivity, plasma, grounding, shielding and EMC, and the physics of electrical safety.

Machine Learning: problem framing and when not to use ML, data work and leakage, the classical toolkit (gradient boosting, linear models, clustering), deep learning fundamentals and architectures (transformers, CNNs, diffusion), the PyTorch/JAX ecosystem and torch.compile, training at scale (DDP, FSDP, tensor/pipeline parallelism, mixed precision), fine-tuning and PEFT/LoRA, honest evaluation, debugging training, inference and serving (vLLM, SGLang, quantization, KV cache), MLOps and reproducibility, hardware and cost, and interpretability, fairness, and safety.

Weather Science: the structure of the atmosphere, radiation and the energy budget, thermodynamics and stability, moisture and clouds, the dynamical balances (geostrophic, thermal wind, vorticity), the general circulation, synoptic meteorology and baroclinic instability, thunderstorms and severe weather, tropical cyclones, the boundary layer, observation, numerical weather prediction including data assimilation and ensembles, forecast verification, predictability and chaos, machine-learning weather prediction, and the weather-versus-climate distinction.

Math and Science Programming: numerical and scientific computing for software engineers — floating-point arithmetic and the errors it causes, conditioning and stability, the BLAS/LAPACK substrate everything stands on, the tool landscape (MATLAB, Python's scientific stack, Julia, R, Fortran, Mathematica) and how to choose, symbolic versus numeric computation, linear systems, ODEs and PDEs, optimization, statistics and uncertainty, high-performance and GPU computing, and the verification, validation and reproducibility practices that separate trustworthy scientific software from plausible-looking output.