CS238 · Fall 2026 · Walla Walla University
Intro to Generative AI
A ten-week, hands-on introduction to how language models work and what to build with them, taught on open models running on your own laptop. No coding or math background required.
About the course
The course follows the instructor's textbook, Illustrating Generative AI, chapter by chapter, with a hands-on lab each week. Students from every major are welcome, and no coding or math background is needed.
Logistics
When and where
Tuesdays and Thursdays, 1:00–1:50 pm, in KRH 327, fall quarter 2026 (September 28 to December 11). No class on Thanksgiving, November 26.
Instructor
Chiké Abuah · chike.abuah@wallawalla.edu
Office hours Mondays and Thursdays, 2:00–3:00 pm, in KRH 329. Email any time; I'm open to feedback about the course at any point.
What you need
A laptop that can run Ollama (8 GB of RAM is workable; 16 GB is comfortable), Python with uv Week 1's lab walks through setup. For heavier models, a shared class server is available under the server guidelines.
Where things live
Labs are in the cs238-labs repository, released week by week. Quizzes, grades, and the textbook are on D2L Brightspace
Materials
Textbook
Illustrating Generative AI by Chiké Abuah. The course follows its chapters in order. The book is posted on D2L for enrolled students as weekly readings (listed in the schedule): one chapter a week; each chapter is a runnable notebook, code and real output side by side. The readings are copyrighted and provided for your own use in this course only; please don't share, post, or distribute them.
Slides and labs
One deck and one lab per week, released as the quarter goes. Labs are written to run on your own Ollama; each ends with reflection questions and a submission checklist.
Schedule
Ten weeks, one topic each. Each week's reading is on D2L. Quizzes are on Tuesday mornings on D2L, and cover the previous week's reading and lab.
| Week | Dates | Topic | Materials | Quiz (Tue) |
|---|---|---|---|---|
| 1 | Sep 29 & Oct 1 | Introduction What generative AI is, what a language model does, and the tools we'll use all quarter. |
Lab 1 · Reading: Introduction · D2L | none |
| 2 | Oct 6 & Oct 8 | Prompting Zero-shot, few-shot, system prompts, chain of thought, and structured output. |
Lab 2 · Reading: Prompting · D2L | Quiz 1 Oct 6 |
| 3 | Oct 13 & Oct 15 | Tokens How text becomes tokens, and why that shapes cost, context, and what a model can see. |
Lab 3 · Reading: Tokens · D2L | Quiz 2 Oct 13 |
| 4 | Oct 20 & Oct 22 | Semantics How embeddings turn meaning into distance, and how semantic search finds what you mean. |
Lab 4 · Reading: Semantics · D2L | Quiz 3 Oct 20 |
| 5 | Oct 27 & Oct 29 | Responsible AI Alignment, jailbreaks, faithfulness, and agentic misalignment. |
Lab 5 · Reading: Responsible · D2L | Quiz 4 Oct 27 |
| 6 | Nov 3 & Nov 5 | Augmentation Retrieval-augmented generation: grounding a model in your own documents. |
Lab 6 · Reading: Augmentation · D2L | Quiz 5 Nov 3 |
| 7 | Nov 10 & Nov 12 | Agentic Tool calling and multi-agent orchestration: giving a model hands. |
Lab 7 · Reading: Agentic · D2L | Quiz 6 Nov 10 |
| 8 | Nov 17 & Nov 19 | Multimodal Vision-language models and prompting for images. |
Lab 8 · Reading: Multimodal · D2L | Quiz 7 Nov 17 |
| 9 | Nov 24 only no Thu class | Efficiency Where the time goes in a model call, and how to pick a model size. |
Lab 9 · Reading: Efficiency · D2L | Quiz 8 Nov 24 |
| 10 | Dec 1 & Dec 3 | Thinking Reasoning models, what a thinking trace is, and when it's worth the wait. |
Lab 10 · Reading: Thinking · D2L | Quiz 9 Dec 1 |
| F | Dec 7 – Dec 11 | Finals week No class meetings. |
— | Quiz 10 open book, take-home |
Dates are subject to change; announcements on D2L take precedence. Thanksgiving is Thursday, November 26; week 9 meets on Tuesday only.
Grading and policies
Labs
One per week, done in class and finished on your own, kept in the cs238-labs repository (clone it once, git pull each week), and submitted as a text file on D2L. Reflection questions are answered in your own words, without a model.
Quizzes
Ten short quizzes on D2L, ten auto-graded questions each. Quizzes 1 to 9 are on Tuesday mornings before class, cover the previous week's reading, lecture, and lab, and allow one fifteen-minute attempt. Quiz 10 covers week 10 and is an open-book quiz done as homework outside class.
Attendance
Class meets twice a week and much of the work happens there. Attendance counts for 30% of the grade; let me know ahead of time when you have to miss.
Late work
Late work may be accepted, but you must make arrangements with me first. If you need to turn something in late, for any reason, email me before the deadline.
Using AI
This is a course about generative AI, and using it is expected. Two lines don't move: reflection questions are yours, written without a model; and every line of code you submit is yours to explain. Say which assistant you used and what for.
Collaboration and integrity
Collaboration on high-level ideas and approach is encouraged; copying someone else's work is not allowed, and any collaboration must be declared at the top of the submission. Academic misconduct is handled under Walla Walla University's academic integrity policy.
Laptops and phones
Lecture days are device-free: laptops closed, phones away, unless an accommodation says otherwise. Lab days are the exception, since the labs are the point of having a laptop. The reason is other people, not you: in a controlled experiment, students who could see a classmate multitasking on a laptop scored lower on the lecture material even though they weren't using one themselves (Sana, Weston, and Cepeda, 2013), and later work found that a peer's inattention spreads to the students around them, lowering their attention, note-taking, and quiz scores, even when the inattentive student sits behind them (Forrin et al., 2021, 2026; Eder, 1982). If you need a device to learn, talk to me and it's fine.
- Sana, F., Weston, T., and Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education, 62, 24–31. doi:10.1016/j.compedu.2012.10.003
- Forrin, N. D., et al. (2021). Attention spreads between students in a learning environment. Journal of Experimental Psychology: Applied.
- Forrin, N. D., et al. (2026). Investigating attention contagion between students in a lecture hall.
- Eder, D. (1982). Peer influence on student attentiveness during classroom lessons.
Accommodations
Students who need accommodations should contact Disability Support Services (DSS@wallawalla.edu, 509-527-2366) and submit a request in the first two weeks of the quarter. Accommodations aren't retroactive, so let me know early and we'll make arrangements.