Mon Oct 19 – Fri Dec 18, 2026 · Monday / Wednesday / Friday · 2 hours/day · in person
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon10/19day 1 | Humanities & Coding · Connotations & Code | Code-along Setup + Variables & data types | D1 opens |
Wed10/21day 2 | — | Code-along Strings & string methods | D1 post |
Fri10/23day 3 | Classification Logic | Code-along Comparisons, conditionals & booleans | R1 due D1 replies |
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon10/26day 4 | Collective Memory | Code-along Lists & loops | — |
Wed10/28day 5 | — | Code-along Functions & dictionaries | — |
Fri10/30day 6 | — (recap) | Work session foundations recap + start HW1 in class | HW1 assigned |
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon11/2day 7 | Data as evidence (brief framing) | Code-along Term frequency ("Meaningful Words") + HW1 debrief | HW1 due HW2 assigned D2 opens |
Wed11/4day 8 | AI Agency | Lab Reading & improving AI code + stylometry seed: Reading for the Seams (close reading) | D2 post |
Fri11/6day 9 | — | Work session HW2 (+ optional C2: term frequency on text of your own) | D2 replies |
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon11/9day 10 | Data Archaeology | Code-along Found data + collection ethics (pandas 01 + scraping) · then get a YouTube API key → YouTube Comment Collector, Step 1 (finish before Friday) | HW2 due |
Wed11/11day 11 | — | Code-along Data cleaning (pandas 02) | — |
Fri11/13day 12 | — | Workshop collect & clean your cultural dataset with the YouTube Comment Collector or Instant Data Scraper (apply Pandas 01–02) → sets up HW3 | — |
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon11/16day 13 | Quantifying connotation (callback to Connotations & Code) | Code-along Sentiment with VADER | R2 due (midterm) D3 opens HW3 assigned |
Wed11/18day 14 | Close vs. distant reading | Code-along VADER deep dive (same notebook, Part 4–5) | D3 post |
Fri11/20day 15 | Predictions on the record | Work session HW3 (frequency + sentiment on your data) | D3 replies Thanksgiving break begins (no class Nov 23–27) |
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon11/30day 16 | NLP & Topic Modeling | Code-along Topic modeling intro (Gensim LDA) | HW3 due |
Wed12/2day 17 | — | Code-along Topic modeling deep · num_topics · limits (same notebook, Part 2–3) | HW4 assigned |
Fri12/4day 18 | Integration (close → distant → close) | Lab Integration demo (frequency + sentiment + topics) via the HW4 notebook + short stylometry demo | Capstone proposal due |
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon12/7day 19 | Going Public | Work session Validation (Checking the Machine) · "being wrong as learning" · capstone framing | HW4 due D4 opens |
Wed12/9day 20 | — | Work session Capstone work session 1 (cultural dataset or stylometry) | D4 post |
Fri12/11day 21 | — | Work session Capstone work session 2 | D4 replies |
| Day | Lecture | Coding | Due |
|---|---|---|---|
Mon12/14day 22 | — | Work session Capstone work session 3 + peer review + presentation run-through | — |
Wed12/16day 23 | — | Presentations Capstone presentations, day 1 | — |
Fri12/18day 24 | — (wrap) | Presentations Capstone presentations, day 2 + wrap | Capstone due R3 due (final self-evaluation) |
Notes on the notebooks: one code-along can span two sessions — the Lists, Loops & Conditionals notebook covers Days 3–4, the VADER notebook spans Days 13–14, and the Topic Modeling notebook spans Days 16–17.
Day 7 "Data as evidence" is a short spoken opener (about 5 minutes) to the term-frequency code-along: the turn from Python foundations to treating text as data.
Notes on lectures: "—" in Lecture marks days with no mini-lecture: recap, workshop, work-session, and presentation days.
Calendar notes: this is the TCU 8W2 (second 8-week) session — Mon Oct 19 → Fri Dec 18, MWF. No class the week of Thanksgiving (Nov 23–27; classes recess after Fri Nov 20 and resume Mon Nov 30). Veterans Day (Wed Nov 11) is a regular class day. The final drop deadline is Thu Nov 19. The schedule will be adjusted to the class's pace; changes announced in class and on TCU Online.