COSC 10001: The Computer Science Experience¶

Fall 2026 · Section 010 · 1 Credit Hour · Seminar Wednesdays, 9:00–9:50 AM · RJH 333

Instructor¶


Instructor	Bingyang Wei
Office	TUC 341D
Office Hours	Monday and Wednesday, 11:00 AM–12:00 PM, or by appointment
Email	b.wei@tcu.edu
Preferred Contact	Email
Response Time	Within 24 hours on weekdays, 48 hours on weekends and holidays. Email sent after 5:00 PM may be answered the next business day.

Class communication channel: a Slack workspace for our section. The invite link is shared through your TCU email on the first day. I use Slack for quick announcements, including cancellations, guest speaker information, and due date changes; quick questions go there too, and anything about grades or personal circumstances goes to email. Install the app and turn on notifications for this workspace so you don't miss time-sensitive updates. Slack is what most software teams use at work, so this is also your first week of practice with it.

Final Evaluative Exercise¶

There is no final exam in this course, and nothing meets during finals week.

Your final evaluative exercise is the Four-Year CS Development Plan: a one-to-two-page written plan, submitted on TCU Online. The due date is in the Schedule.

Student Resources & Policy Information¶

Visit TCU Student Resources & Policy Information for the university resources and policies that support you as a student. Note in particular the sections on Student Access & Accommodation, Academic Conduct, Course Materials, & Safety Policies, and Inclement Weather, Emergency Response & TCU Alert.

Course Description¶

Catalog Description¶

The Computer Science Experience introduces first-year students to the discipline, culture, and professional pathways of computer science. Students explore major subfields of computing (including cybersecurity, artificial intelligence, machine learning, large language models, software engineering, operating systems, and databases) while developing essential academic, professional, and community-building skills. The course emphasizes identity formation, ethical responsibility, industry awareness, and long-term academic planning within the Computer Science, Computer Information Technology, and Data Science programs.

What this course actually is¶

A one-hour-a-week seminar with three jobs:

Show you the whole map. You'll spend the next four years going deep. This course goes wide first, so you can choose deliberately instead of by accident. Security, AI, systems, networks, data, open source: one week each, enough to know whether you want more.
Make you a cohort. You are the CS Class of 2030. You'll be assigned to a small group on day one, you'll work with them all semester, you'll have an upper-level peer mentor, and there will be snacks. Four years is a long time to do alone.
Get you building now. You'll set up a real developer environment, learn Git, learn to drive an AI coding agent, and ship one small thing that works and lives on the public internet under your name, before winter break of your first semester.

Prerequisites¶

None. No prior programming experience is expected or assumed. Some of you have been coding since middle school and some of you have never opened a terminal. Both are normal and both belong here.

Program & Major Connections¶

COSC 10001 is the foundational entry point into the Computer Science, Computer Information Technology, and Data Science majors. Later courses develop technical depth; this course establishes the academic, professional, and community framework that makes that depth possible. It develops professional competencies (GitHub usage, résumé preparation, networking, engagement with faculty and student organizations) that support internship readiness, and it guides you in building a four-year academic and professional development plan.

Course Materials¶

There is no required textbook. Readings and supplemental materials are provided through TCU Online.

Required technology:

A laptop you can install software on, brought to every class. Windows or macOS both work. If you do not have a laptop, email me during the first week. This is a solvable problem and you will not be disadvantaged: the TCU Library runs a laptop loaner program and I will connect you to it. Ask early, not in October.
Free accounts, none requiring payment: a GitHub account and Student Developer Pack, the GitHub Copilot Student plan the Pack unlocks (your primary coding agent), and a ChatGPT free account for the second agent you'll compare it against.

A promise about cost: no assignment in this course requires a paid subscription to anything. Every tool has a free tier sufficient for everything you're graded on. Some classmates will have paid plans; it will not make their work better than yours and it will not show up in your grade. See Tool Setup for what to install and how to get it free.

Learning Outcomes¶

By the end of this course, you will be able to:

	Outcome
SLO 1	Describe major areas of computer science and their societal or industry impact.
SLO 2	Explain how AI and large language models are influencing modern software development.
SLO 3	Demonstrate foundational professional practices (e.g., GitHub, résumé development, LinkedIn presence).
SLO 4	Identify potential academic, research, and career pathways within computer science.
SLO 5	Develop a personalized four-year academic and professional growth plan.
SLO 6	Engage meaningfully in the Computer Science academic and professional community.

How Class Works¶

Every meeting follows the same rhythm. Fifty minutes goes fast; structure protects it. There is no warm-up: we start at 9:00 with a student at the front, so arrive ready to go.

Minutes	Segment
0–5	This Week in CS: three students, one slide and 90 seconds each
5–35	Main topic, guest speaker, or workshop
35–45	Pod activity or live coding-agent demo
45–50	Wrap-up: what's due, what's coming next week

Pods. On the first day you're assigned to a pod of about five students: your default group for the whole semester. You do in-class activities together and share a peer mentor. Sit wherever you like when you walk in; when there's a pod activity, find each other for it. Pods are assigned, not chosen, because you already know how to make friends with people like you and the point is to widen that.

This Week in CS. Once during the semester you'll open class with one slide and ninety seconds about something that happened in computing recently: a launch, a breach, a paper, a lawsuit, a shutdown. Three students go each week, and your date is assigned in the Git session. Not graded on polish, no rubric, and one slide is genuinely one slide. It exists so you start following the field, and so that every person in this room has spoken in front of the class before the semester is over. Peer mentors go first and will do it imperfectly on purpose, so you can see how low the bar is. What to Read is the companion: where to find a story and what to say about it in ninety seconds.

Snacks. There will be snacks. Grab them on your way in, not on the clock. Ingredients are labeled and there's always a nut-free option. Tell me about allergies and dietary restrictions on the Day 1 survey.

Course Requirements¶

Every due date in this course lives in the Schedule, and deliberately nowhere else on this page: one list means there is never a second version to be wrong. Deadlines are on TCU Online as well, and everything is due by 11:59 PM on the listed date unless otherwise specified.

Grade Breakdown¶

Component	Weight
Attendance & Participation	20%
Build Checkpoints (2)	10%
CS Engagement Experiences (3)	15%
Peer Mentor Meeting	10%
Professional Foundations	10%
Ship-It Project + Demo	20%
Final Project: Four-Year CS Development Plan	15%
Total	100%

Attendance & Participation · 20%¶

Assesses SLO 6.

This class meets once a week, so missing one session is missing an entire topic. Your peer mentor takes attendance for your pod each week.

Every student gets one (1) unexcused absence with no penalty. Use it for the week you need it.
Each additional unexcused absence deducts 5 points from your 100-point Attendance & Participation score, so a second one moves that component from 100 to 95: one percentage point off your final course grade.
More than five (5) unexcused absences may result in failure of the course.
Arriving more than 15 minutes late, or leaving early without prior approval, counts as half an absence.

Excused absences (documented): illness, Official University Absence, religious observance, family emergency. See the university attendance policy for documentation requirements. Tell me before class when you can.

Participation means engaging with your pod, taking part in the in-class activity, and delivering your This Week in CS slot on your assigned date.

One activity is worth naming in advance: in the open-source session you will open a real pull request against a live public website, in the browser, and watch it get merged and go live. It's a practice site built for exactly this, so nothing you click can break anything that matters, and the pull request is real either way. It counts here, as participation, not as a separate grade. You'll finish your first semester with a public contribution to open-source software under your own name, which most people manage in their third year, if ever.

Build Checkpoints (2) · 10%¶

Assesses SLO 2, SLO 3.

Two small hands-on builds, 5% each. These are not essays: you build something or take something apart, write down honestly how it went, and hand it in. Both are 🟢 Green: use an AI agent as much as you like. That's the point.

Checkpoint 1: Karel¶

Everything you build in the Karel weeks, handed in as one repository. You've already done most of it in class; this is where it gets submitted.


The beeper program you wrote yourself	The working solution is about five lines. If you have never written code before, this is the assignment that proves you can
A world you built	Use the Edit World button to design your own map, then write a program that solves it. Nobody else will have your world
The agent-extended version	In its own commit, so the history shows who wrote which part
`NOTES.md`	Bullet points, not paragraphs. What you wrote · what the agent wrote · where it got something wrong · what you did about it

Graded by cloning your repository and running it. Most of the points are simply it runs.

Checkpoint 2: Read somebody else's code¶

Every job you'll ever have starts the same way: somebody hands you a codebase you didn't write and you have to find your way around it. Nobody teaches this. You're going to do it once, now, on purpose.

Pick a real open-source project from the approved list (or propose your own, ask me first), clone it, and get to know it. Use your agent. Asking "walk me through how this project is organized" is the single thing coding agents are genuinely, reliably excellent at, which is worth seeing for yourself two weeks after watching one fail.

Submit one Markdown file:


Which project, and why that one	A sentence. Pick something you actually use or are curious about
How it's organized	Five bullets, in your own words, not your agent's. Where does execution start? What are the main pieces? Where would you go to change one thing?
Proof you ran it, or proof you tried	See below
AI Use Statement	Which agent, what you asked, what it got wrong

About that third one. Ideally you get it running and paste in a screenshot. But real software often refuses to run on a real laptop, and that is not you failing, that is the assignment. If it won't start, submit your attempt log instead: what you were trying to do, what you tried in order (including what your agent suggested), what happened each time with the exact error text, and what you think the actual blocker is.

A well-documented failure earns full credit. Not partial credit, not a consolation prize: full credit. A student who fights a broken build for an hour and writes down precisely what happened has learned more, and shown me more, than a student whose project started on the first try. That format is the same one in How to Ask for Help further down this page, because it is the same skill, and it is the one that will make senior engineers glad to help you for the rest of your career.

The only way to lose points here is to submit nothing and say it didn't work.

Budget about an hour. If you're past two, stop and post your log: that is exactly what it's for.

CS Engagement Experiences (3) · 15%¶

Assesses SLO 1, SLO 4, SLO 6.

Attend three approved Computer Science events during the semester. This is how you meet the department.

Approved events include: faculty research talks and departmental seminars; student organization and technical events (Computer Science Society, ACM, Women in Computer Science, Society of Hispanic Professional Engineers); the Industry Advisory Board Meet & Greet; hackathons, tech talks, and other approved CS-related events.

For each event, submit proof of attendance and a 250-word reflection containing all of the following:

A brief summary of the event
The speaker's or organizer's name
One direct quote or specific technical claim you heard
One question you asked, or one you wish you had asked and why
A photo you took at the event
Key insights and their relevance to your development as a CS student

Those specifics exist for a reason: they are things you can only produce if you were actually in the room and paying attention.

There are two checkpoints, one for 2 of 3 and one for all 3; both dates are in the Schedule. The in-class Faculty Research Lightning Talks are not an engagement event; you still need three outside of class.

Peer Mentor Meeting · 10%¶

Assesses SLO 4, SLO 6.

Meet once, for 30 minutes, with your assigned upper-level CS peer mentor.

Submit: three prepared questions before the meeting, and a 250-word reflection afterward summarizing the advice you received and what you'll do with it.

Graded on preparation, engagement, and quality of reflection. Your mentor does not grade you and does not report on you. This meeting is for you.

Professional Foundations · 10%¶

Assesses SLO 3, SLO 4.

Create a GitHub account and get verified for the GitHub Student Developer Pack (start this on day one; verification is not instant)
Create or update a LinkedIn profile
Submit a draft technical résumé
Create one public GitHub repository containing a meaningful README.md and at least one commit
Publish a GitHub profile README introducing yourself

Graded on completion, professionalism, and attention to detail. Your profile README doubles as the icebreaker in the Git session: your podmates will read it.

Ship-It Project + Demo · 20%¶

Assesses SLO 2, SLO 3. Announced in the top-down design session, demoed on Demo Day.

Build and publish one small working thing using an AI coding agent, and document honestly what the agent got right and wrong.

Scope is deliberately small: a weekend of work, not a semester. Pick from the menu (personal website, Discord bot, small command-line tool, data visualization, browser extension, text-based game, study tool) or propose your own.

Deliverables, pushed to your public repository:

File	Contents
The working artifact	It has to actually run
`README.md`	What it does, how to run it, one screenshot
`AI-NOTES.md`	Which agent you used · what it got right · what it got wrong and how you fixed it
2-minute demo	Science-fair format on Demo Day

Rubric: it runs (30) · README quality (20) · AI-NOTES.md depth, especially the failure analysis (30) · demo (20).

Read that weighting carefully. The largest single block of points is for finding and fixing what the AI got wrong. A project where the agent worked perfectly and you learned nothing scores worse than one that broke three times and you can explain why. Full specification in The Ship-It Project.

Final Project: Four-Year CS Development Plan · 15%¶

Assesses SLO 4, SLO 5, SLO 6. No presentation and no final exam.

One document: a written development plan of one to two pages, roughly 600–800 words.

Address: academic goals · skill development goals · internships, hackathons, and summer programs · potential areas of specialization · a realistic four-year trajectory.

One required specific: name one real opportunity you intend to go after. Any of these counts:

a particular internship
a hackathon you plan to enter
a summer research program (many are paid, and some take first-years)
a TCU faculty member whose research you'd want to be part of
an officer role in a CS organization: Computer Science Society, ACM, Women in Computer Science, Society of Hispanic Professional Engineers
a seat in Student Government Association, or leadership in any organization outside CS
peer mentor for this course, doing for the Class of 2031 what your mentor did for you

Say what it is, why that one, and what you'd have to do in the next year to be a plausible candidate. "I'll apply for internships" is not an answer.

Opportunities is the menu, with what exists and, more importantly, when you have to act on it. You are not expected to have known any of this already.

Research is one item on that list, not the expectation. Most computer scientists never work in a lab, and a plan built around an internship and two hackathons is exactly as good as one built around a research group. If you do go the faculty route, the Faculty Research Lightning Talks session gives you five to choose from, and the question you would ask them is your specific.

Evaluated on: clarity and organization · intentionality and feasibility · depth of reflection · professional quality of the writing.

The careers session includes a working session on this plan, so you won't be starting from a blank page in December.

Grading¶

Grades in this course reflect engagement, professionalism, reflection, and intentional academic development. Evaluation emphasizes growth, self-awareness, and participation in the CS community rather than technical mastery or memorization. You are not being graded on how much you already know how to code. Take intellectual risks, ask for feedback, and treat assessment as part of your professional formation.

Letter	Range
A	90–100%
B	80–89%
C	70–79%
D	60–69%
F	Below 60%

Final course grades are rounded up to the next whole number.

Late work: for each day an assignment is late (including weekends and holidays) 15% is deducted. Work more than two days late is not accepted, except for Official University Absences or documented medical reasons. If something is going wrong in your life, email me before the deadline. I am consistently reasonable in advance and consistently unhelpful afterward.

Course Policies¶

Artificial Intelligence: Read This Carefully¶

This course expects you to use AI tools. That is not a loophole; it is the curriculum. One of the six learning outcomes is about how AI and large language models are reshaping software development, and you cannot explain that from the outside. Three rules govern all of it.

1. Disclose. Every submission includes a short AI Use Statement: which tool you used, what you asked it to do, and what you changed. Two or three sentences. Not using AI is a perfectly good statement; just say so.

2. You own everything you submit. If your agent invents a library that doesn't exist, cites a paper that was never written, or produces code that silently corrupts data, that is your error, graded as your error. "The AI said so" is not a defense in this course and will not be one in your career.

3. Respect the Red zones. Some work is deliberately AI-free so that you experience unaided thinking. Every assignment is marked Green, Yellow, or Red:

	Meaning	Where
🟢 Green	Use AI freely	Ship-It project, both Build Checkpoints, résumé drafting, studying
🟡 Yellow	Use AI for outlining, feedback, and proofreading, but the ideas and words must be yours	Event reflections, peer mentor reflection, four-year plan
🔴 Red	No AI	In-class writing

Full policy, rationale, and the AI Use Statement template: AI Policy.

Academic Integrity¶

All submitted work (written, coded, or presented) must represent your own understanding and effort. Plagiarism, unauthorized collaboration, falsification of results, and undisclosed use of AI tools are violations of academic integrity. Note the word undisclosed: in this course, using AI is expected, and hiding that you used it is the violation.

Suspected violations are reported to the Dean's Office of the College of Science & Engineering and handled under the TCU Student Code of Conduct. Sanctions may include a zero on the assignment, a failing grade in the course, and/or additional university disciplinary action. Proper attribution of all sources, collaborators, and digital tools is mandatory.

How to Ask for Help¶

Asking for help early is a professional skill, not an admission of weakness. In rough order:

Your pod: someone next to you has hit the same thing.
The class Slack: post the actual error message, not "it doesn't work." Reply in a thread so the channel stays readable.
Your peer mentor: they took this exact path one or two years ago.
Office hours: Monday and Wednesday, 11:00 AM–12:00 PM, TUC 341D. You don't need a crisis or an appointment. "I'm not sure what I'm doing" is a complete reason to come.
Email: b.wei@tcu.edu, 24-hour weekday response.

A good help request includes: what you were trying to do, what you tried, what happened, and the exact error text.

Accessibility¶

TCU is committed to providing reasonable accommodations. If you have a documented disability, contact Student Access and Accommodation and speak with me early so we can arrange support. If any course activity (hands-on setup, presentations, group work) presents a barrier, tell me and we will find another route.

Course Schedule¶

Every date in this course lives in one place: the Schedule. It has the week-by-week plan and the complete deadline table, and it's posted on TCU Online as well. Deadlines are deliberately not repeated here, so there is only ever one version to trust. Plans may change to improve learning opportunities; changes are announced in class and on Slack.

Welcome to computer science. Let's go build something.