Notes

Short conceptual write-ups for each tool covered in the course. Each note is meant as a 10–15 minute read that complements the hands-on labs and the weekly work distributed through the course LMS.

Available

  • Week 1 — Your first render — source files, rendered outputs, Quarto as the course container, AI as first-pass help, and the Setup conference as the first workflow check.
  • Week 2 — Writing mathematics from source — LaTeX math syntax inside Quarto, inline vs displayed math, the small core vocabulary, rendering as verification, visually inspecting math in the PDF, and AI assistance with verification.
  • Week 3 — Structuring mathematical writing — organizing notation into readable mathematical writing: setup, claim, example, and justification; marking structure with headings and bold labels; avoiding equation-dump writing; inspecting for logic, not just formatting; and AI as a first pass for structure.
  • Week 4 — Figures, tables, and references — the supporting apparatus of a technical document in Quarto: included figures and captions, small tables, citations from a .bib file with an auto-generated reference list, automatic cross-references, inspecting the PDF for apparatus problems, and the Week 4 LaTeX checkpoint.
  • Week 5 — Picking a paper to replicate — starting the two-week LaTeX Project: what “replication” means, choosing a realistic open-access source and verifying it is genuinely open, bounding the scope to one self-contained unit, turning the unit into an annotated outline, and scaffolding a latex-project/ folder that renders a clean skeleton PDF.
  • Week 6 — Finishing the LaTeX Project — closing the two-week LaTeX Project: continuing from the Week 5 scaffold and finishing in the same latex-project/ folder, finishing rather than adding, apparatus on demand (only what the unit needs), reading the rendered PDF as the grader will, common late-week debugging checks, and AI in the finishing week.
  • Week 7 — R foundations in VS Code — opening Module B (R / computation): one Quarto container, two substances — the pivot from typeset math to R-in-Quarto reporting; what an R chunk is; the code + output + prose pattern around every chunk; the render-then-read habit applied to computed output; a tidy dataset, lightly defined; R from VS Code (not RStudio); the R transition conference framing.
  • Week 8 — Visualization with ggplot2 — continuing Module B: one Quarto container, three substances now — a plot joins the chunks and summaries; the grammar of graphics in three words (data + aesthetic mapping + geometry) plus labels; code, plot, and prose in that order around every figure; the render-then-read habit applied to plots; what Week 8 deliberately defers (faceting, themes, scales, ggsave); and AI in Week 8 — what AI can and cannot do with a rendered plot.
  • Week 9 — Simulation and reproducibility — continuing Module B: one Quarto container, four substances now — simulated data joins the chunks, summaries, and figures; why set.seed() is the load-bearing function; the minimum-viable simulation in two chunks; code, output, and prose around every simulation chunk; the render-then-read habit applied to simulated output (render twice, confirm numbers match); a brief note on repeated trials with replicate() and sampling behavior; and AI in Week 9 — what AI can and cannot do with simulation output.
  • Week 10 — The R Project — closing Module B with the R Project: composing your Weeks 7–9 skills into one short focused R-in-Quarto report on a question of your choice; the two named tracks (Track A — data analysis and visualization with ggplot2; Track B — simulation, sampling behavior, or a CLT-style investigation); how to pick a track; what Track A data is allowed; what Track B reproducibility looks like; the required Week 10 R Project conference as project go/no-go; render-twice finishing; and AI in the R Project.
  • Week 11 — A mental model for AI assistants and a verification habit — opening Module D (Generative AI literacy): AI use becomes the substance of the work this week; what an AI assistant is in plain terms (a pattern matcher, not a database or a reasoner); verification over outsourcing; the Verification line of the AI Use Note as the load-bearing line; tool-agnosticism with no paid tier required; the “no detectors” position; privacy carryforward; the Week 11 AI debugging audit shape; pointers to the existing AI use guidelines and AI reading spine.
  • Week 12 — Catching AI hallucinations: a checklist for math, code, and citations — closing Module D (Generative AI literacy): AI as drafter and you as critic and reviser; the five-category hallucination checklist (math / code / citations / prose claims / rendered output consistency); the critique → verify → revise loop; the evidence-grounded Reflection paragraph as a separate artifact from the AI Use Note; tool-agnosticism with no paid tier required; the “no detectors” position carried forward; privacy carryforward; Lab 8 as the workflow walkthrough mapped from debugging to drafting; pointers ahead to the Week 13 Portfolio/workflow conference.
  • Week 13 — Organizing your portfolio folder, the easy way — reopening the workflow thread: what makes a technical portfolio reproducible and legible; source and rendered output together; relative paths; opening the folder, not one file; auditing the term’s accumulated work in place without restructuring it; a one-screen portfolio map; surveying your AI Use Notes as a set; naming your workflow habits; preparing for the required Portfolio/workflow conference; planning the final reflection without writing it; and optional local Git as enrichment, not a requirement.
  • Week 13 — When you’d reach for SageMath, SymPy, or a CAS — an optional second-tool bridge: numerical vs symbolic computing; when a computer algebra system fits better than R; browser-based options that need no install; and what an optional bridge exploration could look like. Enrichment only — no required tool, no required install, no required report.
  • Week 14 — Assembling your final portfolio — turning your organized folder into a coherent, submission-ready final portfolio: the organize → assemble → reflect arc; curating across the four course areas (mathematical writing, computation, workflow, responsible AI use); a final reproducibility/render-verification pass; finalizing the portfolio map as a reader’s guide; becoming submission-ready without submitting; and keeping your Week 13 reflection plan warm without writing the reflection yet.
  • Week 15 — Final polish and the portfolio reflection — closing the course: completing the organize → assemble → reflect arc at reflect; what an evidence-grounded reflection is and grounding every claim in a specific artifact; the four course areas as the reflection’s frame; turning your Week 13 reflection plan into prose; how this reflection differs from the Week 12 AI Use Reflection; the final-polish habit (render, then read the whole portfolio); a high-level note that submission details and the deadline live in the LMS; that there is no traditional final exam; and a brief look back across the course.

The note sequence is complete

These notes span the full course, from your first render in Week 1 to the final portfolio reflection in Week 15. There are no further notes to add — the course concludes with Week 15.

For software install instructions, see Software setup and Lab 1 — Install the stack.