HTML & CSS Foundations
Learn how the web works and build, style and publish your own responsive website with semantic HTML and modern CSS.
Bite-sized courses to build the skills your matched career path calls for.
Learn how the web works and build, style and publish your own responsive website with semantic HTML and modern CSS.
The programming language of the web: variables, functions, the DOM, arrays and objects, and fetching data from APIs.
Load, clean, reshape and explore real data with Python and pandas, then turn the results into clear findings.
Think like a defender: network attack surface, threat modeling, the OWASP Top 10, core controls, identity, cryptography, frameworks and the rules of ethical testing.
Build and run a React Native app on your own phone with Expo: components, navigation, data, storage and device features.
The shared base every STEM career uses: working with numbers and units, testing ideas fairly, handling data and code, and explaining your work.
How civil, mechanical and electrical engineers think, what to study, and the degree, FE and PE route into the field.
Biology, chemistry, the lab mindset, the regulated routes in, and the rules that govern real labs.
How chemists, physicists and materials scientists work: the science and math core, units and estimation, the research path, and how to read and record science.
How statisticians, actuaries and operations research analysts work: the math they use, pairing it with code, credentials, evidence, and explaining results honestly.
Hands-on technical careers you can enter through apprenticeship: troubleshooting, safety awareness, the routes in, and the trade math you will use every day.
The everyday computer, internet, safety and AI skills every tech and STEM job assumes you already have.
Write clear emails and documents, present and run meetings, work well on teams, and navigate résumés, interviews and networking.
The practical math behind tech and STEM work: numbers, algebra, functions, geometry, logic and counting, with short code exercises.
Clean tables, correct formulas, lookups, pivot tables and honest charts in Google Sheets, LibreOffice Calc or Excel.
Use the terminal with confidence, track your work with Git, and collaborate on GitHub with pull requests.
Learn to program in Python from zero: values, decisions, loops, functions, data structures, files, modules and a small data project.
Query, summarise, join and change data in a relational database with SQL, practised in your browser.
Describe data, reason with probability, and draw honest conclusions from samples, with short fill-in-the-blank Python exercises.
Learn how data moves between computers: layers, IP addresses and subnets, ports, DNS, DHCP, HTTPS, and the tools to troubleshoot it.
Recognise lab hazards, read GHS labels and Safety Data Sheets, choose PPE, and understand the training and records that keep labs safe.
Learn your OSHA rights, spot hazards, choose PPE, understand lockout/tagout and electrical safety, and use hand tools, power tools and measuring tools safely.
Read orthographic views, scales, dimensions, tolerances, schematics, GD&T callouts and floor plans, then sketch and model parts in free CAD tools.
Learn hierarchy, layout, type, colour and icons, then build and critique real screens in Figma.
Plan and run small projects: scope, stakeholders, work breakdown, schedules, estimates, risks, status reports and closure.
Atoms, bonding, gases, balanced equations, moles, solutions, pH, buffers, equilibrium and an organic and biochemistry preview, with short fill-in-the-blank Python calculators.
Cells, membranes, the microscope, DNA and inheritance, microorganisms, blood and the immune system: the biology every lab career builds on.
Understand tech roles and career ladders, pick a realistic learning route, build portfolio evidence, and navigate postings, interviews and your first 90 days.
Build interactive interfaces with React components, props, state, effects, context, routing and component tests.
Build interfaces that work for everyone on every screen: WCAG 2.2, keyboard and ARIA, fluid layouts, responsive images and real audits.
Measure efficiency with Big-O, then use searching, sorting, hash maps, stacks, linked lists, trees, graphs and dynamic programming in Python.
Design REST routes, validate JSON, build Node and Express APIs on a SQL database, secure them, test them and ship them.
Go beyond the basics with subqueries, CTEs, window functions and the analytics patterns analysts use every day, practised in your browser.
Turn analysis into charts people read correctly: visual principles, matplotlib and seaborn, small multiples, dashboards and a short data story.
Run a Linux server with confidence: users and permissions, services, packages, logs, SSH keys, bash scripts and scheduled jobs.
Learn how the public cloud works: service models, regions, shared responsibility, compute, storage, networking, IAM, secrets and cost control, using free tiers only.
The calculus and linear algebra behind science, engineering and machine learning: derivatives, integrals, vectors, matrices, gradients and eigenvalues, with Python exercises.
The physics behind engineering and the physical sciences: motion, forces, energy, momentum, torque, circuits, induction, waves and heat, with Python exercises and a home pendulum lab.
Use NumPy arrays, plots, fitting, numerical methods, units and instrument data files to do real engineering and science calculations in Python.
Model uncertainty with random variables and distributions, then estimate, test and update beliefs from data, with Python simulations you run in the browser.
Learn how machines learn from data: implement regression, trees, metrics, k-means, PCA and anomaly detection from scratch in NumPy, and practise honest evaluation.
Discover what a business really needs and turn it into clear requirements, process maps, user stories, data models and a gap analysis.
Deliver work in short, steady cycles: agile values, Scrum roles and events, Kanban flow, backlogs, sprints, retrospectives, metrics and tools.
Research real users, define the problem, design and prototype a solution, test it and write it up as a portfolio case study.
Analyse why games work, build and playtest paper prototypes, balance systems and levels, and communicate a design with a one-page GDD and a pitch.
Use the science of learning to design lessons, objectives, materials and assessments that actually change what people can do.
Learn DC and AC circuit analysis, power factor and three-phase basics, safe measurement on battery circuits, simulation, transformers, motors and systematic troubleshooting.
Statics, strength of materials and an introduction to dynamics: equilibrium, trusses, section properties, stress and strain, beam diagrams, bending and deflection, F = ma, vibration and factors of safety, with Python exercises.
The laws of thermodynamics, steam tables, power and refrigeration cycles, fluid statics, Bernoulli, pipe losses, heat transfer, R-values and heat exchangers, with Python exercises.
How the structure of metals, ceramics, polymers and composites sets their properties: crystal structure, defects and diffusion, mechanical, thermal and electrical properties, failure, phase diagrams, heat treatment and materials selection.
Core bench skills and instruments: balances, glassware, pipetting, buffers, centrifuges, chromatography, spectrophotometry, calibration, microscopy and aseptic technique.
Keep trustworthy lab records, query LIMS data, run QC with Westgard rules, build calibration curves, estimate uncertainty, and work within SOPs, CAPA and accreditation.
Extract nucleic acids, run PCR and qPCR, read gels, Western blots and ELISAs, compare sequencing methods, and work with sequences and BLAST.
Learn how bearings, belts, chains, couplings, gears, hydraulics, pneumatics and pumps work, how they fail, and how maintenance teams lubricate, plan PM work, rig loads and weld safely.
Go from building components to shipping production front-ends: architecture, TypeScript, state, performance, testing, CI and code review.
Design, test, refactor, review, estimate and run software the way professional teams do.
Take a React Native app to production: architecture, offline data, secure auth, testing, performance, accessibility and store releases.
Ship and run cloud software safely: containers, CI/CD pipelines, Terraform with cost guardrails, SLOs, alerting and incident response.
Design, tune, operate and secure production databases: normalisation, indexing, backups, replication, access control, monitoring and safe migrations.
Run day-to-day defense like a SOC analyst: logging and SIEM hunting, IDS alerts, incident response, triage, forensics, vulnerability management, hardening, cloud posture and MITRE ATT&CK.
Work like a mid-level data analyst: define KPIs, forecast, run and analyse A/B tests, model analytics tables and turn stakeholder requests into recommendations.
Go from classic ML to the models used at work: neural networks, embeddings, CNNs, gradient boosting and LLM apps, plus evaluation, experiment tracking and a capstone.
Take models from notebook to production: reproducible training, serving APIs, retrainable pipelines, CI/CD for ML, drift detection, monitoring and governance.
Fit and check multiple regression and GLMs, design randomised, blocked and factorial experiments, and turn analyses into clear, reproducible reports for the researchers you work with.
The core mathematics of the actuarial profession: interest theory, life contingencies, loss models, credibility and ratemaking, plus how to plan the SOA and CAS exams.
Model real decisions with linear and integer programming, networks, queues, simulation and decision trees, then present the results so managers act on them.
Design how business systems fit together: map the landscape, draw data flows, choose build or buy, specify integrations and data migrations, and deliver with UAT and change management.
Lead mid-size IT projects: hybrid delivery, governance, earned value, vendors, business cases, technical and security risk, recovery and your path to PMP and program management.
Build design tokens and component specs, hand designs to engineers with clear annotations, and measure and iterate after launch.
Build playable prototypes in code and in Godot: game loops, input, collision, physics, state machines, data-driven tuning, jams and publishing.
Facilitate live and virtual sessions, build onboarding programs and an LMS course, and prove what your training changed.
Teach programming well: diagnose novice misconceptions, use PRIMM, pair programming and Parsons problems, plan standards-aligned units, assess code fairly and navigate teacher certification.
How engineering work is really done and licensed: project phases, calculation packages, specs and submittals, codes and standards, QA/QC, the FE and PE, and ethics.
Load combinations, steel and reinforced concrete beams, soils and bearing capacity, stormwater runoff, Manning's equation, surveying, transportation, civil CAD and BIM, and construction administration.
Size shafts, bolted joints and bearings, model parts parametrically, read GD&T, sanity-check FEA, choose manufacturing processes, design for manufacturing, compute Cpk and prepare parts for 3D printing.
Diodes, transistors and op-amps, digital logic and microcontrollers, spectra, filters and PID control, the power grid, per-unit and load flow, protection, inverters and PCB layout.
Read and apply the National Electrical Code: navigation, definitions, adoption, conductor sizing, voltage drop, load calculations, box fill, grounding, GFCI/AFCI, motors and exam prep.
Read relay ladder diagrams, match sensors and actuators, understand VFDs, program PLC logic with timers and counters, and troubleshoot, guard and maintain automated machines.
Calculate results from titrations and gravimetry, compare methods statistically, read chromatograms and spectra, validate methods to ICH Q2, plan sampling, and work in GMP, GLP, EPA and ISO 17025 labs.
Protein structure and purification, exploring PDB structures, enzyme kinetics and inhibition, binding and thermodynamics, spectroscopy, structural biology, molecular simulation and research career routes.
Work like a medical laboratory scientist: accept or reject specimens, read chemistry, hematology, microbiology and blood bank results, call critical values, run daily QC and plan your certification.
Special relativity, quantum and nuclear physics, Monte Carlo, orbit and PDE solvers, fitting with uncertainties, data acquisition and research computing, all in Python.
X-ray diffraction, SEM and TEM, DSC and TGA, tensile, hardness, fatigue and fracture testing, ASTM methods, polymer, ceramic and thin-film processing, and materials databases.
Culture cells aseptically, count and passage them, control contamination, model growth, understand bioreactors and purification, and work under GMP with validated systems and batch data.