ENGLISH · BEGINNER FIRST · ORIGINAL ARK TEACHING
Launch with seven accessible introductions and three curiosity-led science stories. Then build consecutive beginner lessons so each playlist becomes a useful learning sequence.
ARK: subject → course → section → lecture, with guided practice, independent work, checkpoints, section tests and a capstone. Save an outline to activate the existing private learning-path system.
YouTube: one playlist per course, videos in lecture order, section breaks in descriptions, and links back to the matching ARK activity. Use the same course and lecture IDs in the production ledger. The first ten are a launch sampler; the catalogue order remains the teaching order.
Every lecture needs one measurable outcome, one visual explanation, one clearly explained real-world example and one check-for-understanding. Three minutes is the initial microlecture target; split overloaded topics into a sequence before scripting. Never compress an advanced proof merely to hit a duration.
MATH-01 · ~3 MIN · NOT PRODUCED
Opening: Two pencils meet three more. What changed?
Visual: Two labelled groups move together, then become 2 + 3 = 5.
ARK practice: Draw 4 red counters and 2 blue counters; count and explain the total.
Review focus: Zero changes the notation but adds no objects.
Course: Joining two groups →PHYSICS-01 · ~3 MIN · NOT PRODUCED
Opening: You sit still, but your position keeps changing.
Visual: Compare a passenger against the bus seat and the roadside.
ARK practice: Draw the same passenger in two reference frames.
Review focus: Always name the reference; do not imply rest is absolute.
Course: Motion relative to a reference →CHEMISTRY-01 · ~3 MIN · NOT PRODUCED
Opening: One substance can keep a shape, flow, or spread.
Visual: Compare particle arrangements and motion with a clear model disclaimer.
ARK practice: Match three particle sketches to states and justify each match.
Review focus: Particles are not drawn to scale; liquid particles remain close together.
Course: Particle model →BIOLOGY-01 · ~3 MIN · NOT PRODUCED
Opening: A leaf and your skin have something in common.
Visual: Zoom from organism to tissue to a simple labelled cell.
ARK practice: Order organism, organ, tissue and cell by scale.
Review focus: Do not imply every cell has a nucleus or every organism has organs.
Course: Cells →TECHNOLOGY-01 · ~3 MIN · NOT PRODUCED
Opening: A click starts a chain you usually cannot see.
Visual: Input → processing → output, using a calculator button.
ARK practice: Map the input and output of a familiar device.
Review focus: Keep hardware, software and user roles distinct.
Course: Inputs →AI-01 · ~3 MIN · NOT PRODUCED
Opening: Two systems sort fruit, but they learn their rules differently.
Visual: Compare an explicit colour rule with a toy labelled-example classifier.
ARK practice: Classify three fictional tools and state what evidence is missing.
Review focus: Learning patterns is not proof of understanding or correctness.
Course: Rules versus learned patterns →PYTHON-01 · ~3 MIN · NOT PRODUCED
Opening: Make a computer display one line you chose.
Visual: Code, instruction pointer and output panel; type one small change.
ARK practice: Write two print statements and predict both output lines.
Review focus: Use a named supported Python 3 version at production time; explain quotes.
Course: The print function →DISCOVERY-01 · ~3 MIN · NOT PRODUCED
Opening: A small Moon can hide a much larger Sun.
Visual: An original labelled alignment and shadow diagram, not to scale.
ARK practice: Move a Moon marker into the alignment that blocks sunlight.
Review focus: Explain apparent size and include official eclipse-viewing guidance before release.
Course: Why a solar eclipse happens →DISCOVERY-02 · ~3 MIN · NOT PRODUCED
Opening: Two accurate clocks need not accumulate equal time.
Visual: A simple light-clock comparison with labelled observers.
ARK practice: Identify which claims are measured effects and which are speculation.
Review focus: Time dilation is established; practical travel into the past is unproven.
Course: Why moving clocks can disagree →DISCOVERY-03 · ~3 MIN · NOT PRODUCED
Opening: The destination keeps moving while the spacecraft travels.
Visual: Earth and Mars advance while an illustrative transfer arc appears.
ARK practice: Explain why aiming at Mars’s current position would miss the future target.
Review focus: Verify mission claims at production time; label the orbit diagram as simplified.
Course: Launch windows →Suggested sustainable starting cadence: two reviewed videos per week. Ten videos would occupy five release weeks once production is ready. This is a planning assumption, not a delivery promise; measure actual production effort on the first ten before committing a calendar.
Mathematics: Build the picture, explain the rule, work an example, then justify it. Visual constructions, worked problems and proofs.
Physics: Predict, observe a demonstration, draw a model, then test its limits. Diagrams, virtual experiments, data analysis and simulations.
Chemistry: Connect visible observations, particle models and chemical notation. Molecular models, reaction accounting and supplied laboratory data.
Biology: Zoom from organism to mechanism, then evaluate the biological evidence. Annotated systems, sequence analysis and observational investigations.
Technology: Follow a real task through a system, then design and troubleshoot it. System diagrams, design reviews and bounded prototypes.
Artificial Intelligence: Begin with a baseline, trace a model, measure errors and improve it. Data experiments, evaluations, model tracing and reproducible projects.
Python: Predict the output, trace state, write a small program and debug it. Coding, trace tables, tests and original portfolio projects.
Curiosity Lab: Open with a question, reveal the mechanism, distinguish evidence from speculation. Visual explanations, evidence checks and mission tradeoffs.
Project Management: Start with a delivery problem, build the project artifact, simulate a change and defend the decision. Project charters, schedules, risk registers, delivery simulations and benefits reviews.
Economics: State the question and assumptions, draw the model, analyse evidence and test competing explanations. Economic diagrams, synthetic datasets, calculations and evidence-based policy memos.
Finance: Trace cash flows, calculate a transparent model, stress-test assumptions and explain risk. Fictional USD budgets, statement analysis, valuation models and risk scenarios.
Business Administration · BBA/MBA: Study an original business case, compare options, make a decision and defend implementation. Case discussions, business plans, management simulations and original consulting projects.
No video generation, paid API calls, YouTube connection or uploads are started by browsing or saving this catalogue. Existing server topic policy, spending caps and private review requirements remain in force.
Mathematics: 24 courses · 72 sections · 616 lecture topics.
Physics: 16 courses · 48 sections · 400 lecture topics.
Chemistry: 14 courses · 42 sections · 343 lecture topics.
Biology: 14 courses · 42 sections · 341 lecture topics.
Technology: 14 courses · 42 sections · 339 lecture topics.
Artificial Intelligence: 14 courses · 42 sections · 343 lecture topics.
Python: 12 courses · 36 sections · 312 lecture topics.
Curiosity Lab: 3 courses · 9 sections · 65 lecture topics.
Project Management: 12 courses · 36 sections · 288 lecture topics.
Economics: 12 courses · 36 sections · 288 lecture topics.
Finance: 12 courses · 36 sections · 288 lecture topics.
Business Administration · BBA/MBA: 18 courses · 54 sections · 432 lecture topics.
This is a broad first-edition curriculum spine, not a claim to contain every theorem, organism, subdiscipline, software library or current research result. Research courses are entry maps; they require deeper specialist sequences. No Harvard, Oxford or MIT affiliation, accreditation or equivalence is claimed.
Before producing each course, audit its prerequisites, objective-to-question alignment, accessibility, factual sources and topic granularity. Keep a gap register. Initial specialist expansion areas include algebraic geometry and advanced number theory; quantum field and particle theory; medicinal and advanced synthetic chemistry; organism-specific biology; compiler and distributed-system depth; AI learning theory and current models; and Python ecosystem specialisations. These must receive full sections and microlectures before being described as complete.
Original ARK outlines use these public references to check breadth and sequencing. Sources were inspected on 11 October 2026. Course material, lecture scripts, images and assessment banks have not been copied. Recheck facts and reuse rights during production.
General-management core breadth and case-based learning reference; no affiliation or degree equivalence.
Project-management educational breadth; ARK outlines and assignments are original, not copied certification materials.
Principles-to-intermediate progression and model-based analysis reference.
Degree-stage and specialist-pathway reference; no affiliation or equivalence claim.
Matrix theory and linear algebra scope.
Proof-based analysis scope.
Foundational mechanics reference.
Quantum foundations reference.
Analytical and experimental-method coverage.
Genetics progression reference.
Computer-science breadth and competency reference.
Beginner programming and project practice reference.
Search, reasoning, uncertainty and learning reference.
Language scope; check versions when producing lessons.