Syllabus

MATH 395.02 Creating with AI in the Loop

Hope College - Spring 2026

Course Information	Details
Location	VZN 298
Times	1:30-2:50pm (TR)
Credits	3
Instructor	Brian Yurk
Email	yurk@hope.edu
Office	VWF 215
Office Hours	M 10:00-10:50, W 12:00-12:50, R 11:00-11:50, or by appointment

Course Description

This course offers an introduction to generative AI in modern software development, combining hands-on Python work with a clear conceptual understanding of how large language models behave in practice. Students develop/strengthen their Python skills while learning how these models work, what they can and cannot reliably do, and how to interact with them effectively. Emphasis is placed on generative AI literacy: designing prompts and interfaces that elicit useful behavior, understanding model limitations, and reasoning about reliability, uncertainty, and evaluation in AI-assisted systems, alongside broader considerations of ethics, privacy, bias, and real-world risks. The course also explores AI-assisted programming across a spectrum, from coding assistants and “vibe coding” workflows to agentic tools that plan and execute multi-step tasks, culminating in the creation of applications that integrate LLMs to solve real problems.

Prerequisites: CSCI 115, or CSCI 125, or MATH 313, or significant programming experience (with instructor permission)

Instruction

Class meetings will combine brief, topic-driven instruction with hands-on work: we will use short mini-lectures and demonstrations to introduce new ideas and tools, then practice/explore them through programming/build assignments. Class time will also be dedicated to writing brief reflections and discussing broader generative AI concerns, such as AI ethics, privacy, bias, and real-world risks. Your final project group will organize and lead one of these discussions.

Outside of class, time will be spent completing build assignments, including documenting your process, reasoning, and learning, as you develop with AI tools. A major emphasis of the course is learning to read, evaluate, and improve code, so significant out-of-class effort should be dedicated to this, including preparing for individual and group code reviews. Throughout the semester you will also spend time outside of class consuming resources (reading articles, watching videos, etc.) in preparation for in class reflection and discussion.

The final weeks shift toward group project work: maintaining a well-organized project repository, preparing a polished presentation, producing a public-facing, portfolio-ready artifact, and completing a final group code review.

Mandatory AI use. Because this course is specifically about developing responsible, effective AI-assisted software development skills and creating software that integreates generative AI, students are required to use approved generative AI tools. Altenative assignments that do not require the use of generative AI will not be available.

Course resources will be available through our course webpage https://ai-in-the-loop-2026.github.io/ai-in-the-loop-hub/ (primary) and Moodle (secondary). Assignments will be submitted using GitHub Classroom. Occasionally, we may also use Moodle for assignment submission.

Other requirments. Students are required to have the following:

A fairly recent Mac or Windows laptop that you can install software on (iPads or Android tablets, Chromebooks, etc. are not sufficient/supported) for working on assignments in and out of class. Linux is welcome, but self-supported
GitHub account for accepting and submitting assignments, developing and maintaining code repositories
Personal Google account (separate from .edu account), like a GMail account, for accessing Google AI Studio and other resources.
Software necessary for the course installed on your laptop. This includes VS Code with various extensions, Python development tools, various Python packages, Gemini CLI, etc. You do not need to set this up before the class starts
An API key for using Gemini models. You do not need to set this up before the class starts.
A public website (github pages) “portfolio piece” that summarizes/demonstrates your final project. You do not need to set this up before the class starts, and there is no hosting cost

Use of other generative AI tools. We will primarily use Google/Gemini generative AI tools. You are encouraged to responsibly explore other free and paid generative AI tools (e.g., Claude Code, Codex, Anthropic or OpenAI API, Cursor, etc.) when it is appropriate in the course. However, your instructor will not typically provide technical support for these tools.

Evaluation

Grades will be determined as follows:

Assignment Type	Weight
Attendance, in-class participation	10%
Written reflections (8-10)	5%
Build assignments (8)	20%
Individual code reviews (2)	30%
Group-led discussion	5%
Final project repository	5%
Final project presentation	5%
Final project “portfolio piece”	5%
Final project group code review	15%

Grading Scale

Your final letter grade will be determined using the following scale:

Grade	Range	Grade	Range	Grade	Range
A	93-100%	B-	80-82%	D+	67-69%
A-	90-92%	C+	77-79%	D	63-66%
B+	87-89%	C	73-76%	D-	60-62%
B	83-86%	C-	70-72%	F	0-59%

Attendance & Participation

Attendance is very important to your success in this class and is considered mandatory. If you must miss a class (illness, scheduled college event, family matters, etc.) you should inform your instructor ahead of time if at all possible.

Final Exam Date

The final exam for this class (group code review) is on Monday, May 4 from 12:30-2:30pm.

Special Note: Do not arrange travel without confirming the dates of your final exams/projects, as dictated by the Office of the Provost.

Schedule

Course schedule with weekly details

Important dates

Activity	Dates
Individual Code Review 1	Feb. 19-20, 23
Individual Code Review 2	March 23-26
Final Project Presentations	April 30
Group Code Review	May 4

Note: You will set up an appointment for indvidual code reviews on one of the listed dates. Group code reviews will serve as our final exam–each project group will sign up for a time slot during the scheduled exam period.

Policies & Statements

AI Use Policy (click to expand)

Use of Generative AI

Overall Course AI Status: 🟡 Yellow — The use of specific generative AI tools is required for many of the assignments in this class. However, there are some activities for which generative AI tools are not allowed.

On programming assignments where it is allowed, it is important to treat AI as a tool, not a replacement for understanding your code.

Written Reflections — 🔴 Red (AI not allowed)

Throughout the course you will be asked to read articles, watch videos, and reflect on your learning in writing. You may not use generative AI tools to help with these written reflections.

Why? These reflections are intended to help you think and capture your personal understanding and growth. Using AI to generate content for these reflections undermines the purpose of the assignment.

Build Assignments — 🟢 Green (Encouraged, with caution)

You may use generative AI tools to help write code for Build Assignments. You are also encouraged to use AI to help you understand code provided by the instructor or code that was written with AI assistance.

Most Build assignments will require you to complete an AI development log, documenting your goals, prompts, AI responses, code changes, and testing results.

Why? One of the primary goals of this course is to prepare you for real-world software deveopment, where AI tools are becoming common. Learning to use AI effectively and responsibly is an important skill.

Use caution: It can be tempting to hand your coding task off to an AI tool without understanding the results. You are the developer—AI is your assistant, not the other way around. You are responsible for making design decisions, specifying what the code should do, and understanding how it works. AI can help with implementation details, but the high-level thinking and decision-making must be yours. You are responsible for your code and what it does.

Code Reviews - During the Review — 🔴 Red (AI not allowed)

Code Reviews will include giving a short presentation and answering questions about your code, design decisions, etc. You may not use generative AI during the presentation or the question and answer session–you must understand your code and be able to answer questions about it without AI assistance.

Why? These assessments measure your understanding. If AI does the thinking, grades do not reflect what you can do, and that hurts you in later courses and in the real world. Using AI on red-light assessments is academic dishonesty.

Code Reviews - Preparing for the Review — 🟢 Green (Encouraged, with caution)

You may use generative AI tools to help prepare for the Code Reviews. For example, you may use AI to help you understand code that was provided to you by the instructor or code that was written with AI assistance. You may also use AI to help you practice explaining your code or answering potential questions.

You may use AI to help you create your slides for the presentation component of the Code Review. If you use AI for this purpose, your presentation must include a slide describing how you used it. You must also submit a separate log of your AI interactions while working on the slides (e.g., the prompts and responses and how they were integrated into your presentation).

Why? Preparing for a Code Review is about learning and understanding. AI can be a great tool for this if used properly.

Use caution: Always ensure that you fully understand any explanations or code generated by AI. You should be able to explain everything in your own words during the review. You are responsible for the content of your presentation and your answers during the Q&A.

Final Project Presentation - During the Presentation — 🔴 Red (AI not allowed)

Final Project Presentations are given to the whole class (and possibly guests) and focus on the problem you addressed, your solution, and what you learned. You may not use generative AI during the presentation or the question and answer session—you must be able to explain your project and answer questions without AI assistance.

Why? These presentations measure your ability to communicate your work. You should be able to articulate the problem, your approach, and your results in your own words.

Final Project Presentation - Preparing for the Presentation — 🟢 Green (Encouraged, with caution)

You may use generative AI tools to help prepare for the Final Project Presentation. For example, you may use AI to help you organize your ideas, practice explaining your project, or anticipate audience questions.

You may use AI to help you create your slides. If you use AI for this purpose, your presentation must include a slide disclosing how you used it.

Why? Preparing for a presentation is about organizing and refining your message. AI can be a helpful tool for this if used properly.

Use caution: The presentation should reflect your understanding of the problem and solution. You should be able to explain everything in your own words. You are responsible for the content of your presentation and your answers during the Q&A.

Final Project Repository — 🟢 Green (Encouraged, with caution)

You may use generative AI tools to help write code for your final project. You are also encouraged to use AI to help you understand code that was written with AI assistance.

Your final project repository must include an AI development log documenting your goals, prompts, AI responses, code changes, and testing results throughout the project.

Why? The final project is an opportunity to apply what you’ve learned about working effectively with AI tools on a larger, self-directed project.

Use caution: Just as with the Build Assignments, it is important to remember that you are the developer and AI is your assistant. You are responsible for making design decisions, specifying what the code should do, and understanding how it works. AI can help with implementation details, but the high-level thinking and decision-making must be yours. You are responsible for your code and what it does.

Final Project Portfolio Piece — 🟢 Green (Encouraged, with caution)

Your final project portfolio piece is a public website summarizing/demonstrating your project. It is intended to showcase your work and your skills to potential employers, collaborators, and the broader community.

You may use generative AI tools to help create the content for your portfolio piece. If you use AI for this purpose, your portfolio piece must include a section disclosing how you used it.

Why? Creating polished, professional content is a valuable skill. AI can help with writing, design suggestions, and refining your message—skills you’ll use throughout your career.

Use caution: The portfolio piece should authentically represent your skills and experience. Ensure that you fully understand and can explain all of the content. You are responsible for the content of your portfolio piece, which is available publicly on the web.

Things You Should Never Do with AI — 🔴 Red

Share sensitive personal information (yours or others’): student ID, financial info, detailed health info, etc.
Upload or share quizzes, tests, or exam questions with AI tools.
Use AI to evade policies (e.g., “rewrite this so it passes plagiarism detectors”), break the law, or violate privacy.
Treat AI as automatically correct; always check it against course materials and your own understanding.
Represent AI-generated work as entirely your own when it is not.

With Great Power Comes Great Responsibility

AI is a powerful tool that can greatly enhance your learning and productivity. However, it also comes with responsibilities. Always use AI ethically and in accordance with course policies.
Other courses may have different AI policies, often more restrictive than ours. In fact, many courses ban the very tools we encourage here. It is your responsibility to understand and follow the policies for each course you are enrolled in.

When in doubt about whether a particular use of AI is appropriate, always ask your instructor.

Transparency: How I Use AI as Instructor

I use AI tools extensively in developing this course. For example, I use AI to:

Draft and refine course documentation, policies, and resource guides
Create and organize course website content
Verify technical instructions are accurate and up-to-date
Draft and clarify assignment instructions
Help write code for assignments
Draft and refine slides

I always review and edit AI-generated content before it reaches you. Given the nature of this course, I may even experiment with using generative AI to assist with grading, but I am responsible for the results.

Collaboration Policy (click to expand)

Build Assignments

On Build Assignments, you are encouraged to discuss concepts, approaches, and code with your classmates. All code you submit must be written by you, with or without AI assistance—not copied from classmates, etc. You are responsible for understanding and being able to explain all code you submit.

Individual Code Reviews

You may seek feedback from classmates while preparing for Individual Code Reviews, including feedback on your slides. However, that feedback must not extend to writing any part of your presentation.

Written Reflections

Written Reflections are to be completed individually without collaboration.

Final Project and Group Code Reviews

The Final Project is a group effort. You may discuss ideas with classmates outside your group, but all code must be written by your group members (with or without AI assistance). Each group member must understand and be able to explain all code in the repository.

You may seek feedback from classmates outside your group on your presentation, Portfolio Piece, and Group Code Review slides, but that feedback must not extend to writing any part of these deliverables.

Final Project Group Evaluation

Each group member is expected to contribute fairly to the Final Project. At the end of the project, each group member will complete a confidential evaluation of their own and their teammates’ contributions. If a group member did not contribute fairly, their grade may be adjusted accordingly.

Late Work Policy (click to expand)

Late Build Assignments

You may have a single late submission (at most 48 hours late) of a Build Assignment (excluding A5 and A9) without penalty. To use this late submission, you must notify the instructor by email before the assignment due date and time. If you do not notify me in advance, late submissions will be penalized according to the standard late policy below. A5 and A9 must be submitted by the deadline to facilitate Code Reviews.

After using your single late submission, any further late submissions for Build Assignments will be penalized at a rate of 10% of the total assignment points per 12-hour period (or fraction thereof) late. For example, if an assignment is worth 100 points and you submit it 26 hours late, you will lose 30 points (10% for the first 12 hours, 10% for the second 12 hours, and another 10% for the additional 2 hours).

Written Reflections

Written Reflections will be completed in class, and late work will not be accepted. Your lowest Written Reflection score will be dropped at the end of the semester to accommodate for any unforeseen circumstances.

Code Reviews, Group-Led Discussion, and Final Project Presentation

Code Reviews, the class discussion your group leads, and the Final Project Presentation must be completed at the scheduled times.

Final Project Deadlines

Submissions related to the final project (e.g., proposal, code submission, portfolio piece, etc.) must be submitted by the specified deadlines. Late submissions will be penalized at a rate of 20% of the total points per 12-hour period (or fraction thereof) late.

Exceptions

Exceptions to the late work policies outlined above will only be made for excused absences, as defined by Hope College policies. If you believe you have a valid reason for an exception, please contact the instructor as soon as possible to discuss your situation.

Diversity, Equity, and Inclusion Statement (click to expand)

It is my intention that every student has the opportunity to grow and flourish in this class. A crucial part of this is that each and every student deserves to feel safe and that she or he belongs in the class. Each of us has a role in working toward creating an inclusive environment, even if doing so requires us to speak out and causes us discomfort sometimes.

The diversity that students bring to this course is viewed as an asset, and this course will function in a manner that respects and values that diversity, including race, ethnicity, gender identity, sexuality, disability, age, socioeconomic status, nationality, religion, and culture. Please let me know if anything said or done by the instructor or other students in the class leads to hurt or offense. Such actions, even when unintentional, are deserving of attention.

Racist and discriminatory policies and ideas present obstacles to student flourishing and do not reflect the values of this course. It is my intention that this course and its policies promote equal representation and equitable outcomes among groups. Please let me know if you have ideas for improving this course or its policies in ways that make it more effective for you or for other students or groups. I value your perspective, and I take it seriously.

Other Policies & College Resources (click to expand)

Accommodations

If you have questions about access or are a student needing accommodations for a disability, please contact me. I will ask that you connect with Disability and Accessibility Resources if you haven’t already.

Academic Honesty & Integrity

As it seeks to fulfill its mission, the Hope College community assumes each of its members will operate with integrity and honesty, with a sense of personal responsibility, and with mutual trust and concern toward others in all facets of the life of the college. In order to apply this principle to academic life in a fair and consistent manner, the following policies have been adopted to clarify the expectations regarding conduct, and to establish a set of procedures for dealing with situations which violate these expectations.

-Preamble, Code for Academic Integrity at Hope College

More information about Academic Integrity can be found at: https://hope.edu/offices/student-development/policies-resources/student-handbook.html#academic-integrity

Short-Term Absence Policy

Hope College recognizes that life events may unexpectedly interrupt an academic semester, including needing time away from campus. Thus, the purpose of a formal process for short-term, temporary absence is to improve the student experience so that they may continue progress in a course of study if unable to attend and participate in person while seeking treatment and/or recovering from a medical or mental health event, a family emergency/crisis, or other extraordinary circumstance. View the entire Short-Term Temporary Absence Policy.

If a situation arises (such as medical treatment or family bereavement) that requires a longer absence, please complete the short-term absence form to ensure that appropriate documentation is provided to the CARE team.

Excessive Absence Policy

Hope College encourages students to regularly attend class and allows faculty to develop their own classroom attendance policies. Attendance and participation in class are vital components of a residential college experience. View the entire Excessive Absence Policy.

The Hope Health Center does not provide medical excuses for missed classes, exams, or assignments, as medical conditions are confidential and often not verifiable. This is in alignment with the Academic Medical Excuse Policy and consistent with the recommendations of the American College Health Association. Thus, instructors cannot request documentation from the Hope Health Center.

Special Note: Only arrange holiday travel after confirming the dates of your final exams/projects, as the Office of the Provost dictates.

Student Complaint

Hope College is committed to the appropriate resolution of complaints as efficiently and effectively as possible. Providing a mechanism to hear complaints allows us to improve our services. Students are encouraged to speak directly to other Hope community members to resolve conflict and/or seek an informal resolution of the dispute directly with the other community member(s) whenever possible. Please use this Complaint form when such a resolution is impossible.

Safety & Emergency Preparedness

Students should dial 911 (the United States’ primary emergency response system) from any phone if they or someone else experiences a medical or mental health emergency. Students can also contact Hope College’s Campus Safety Office (616-395-7770) in any kind of emergency situation, and Campus Safety will contact the necessary emergency response service. You can learn more about specific emergency instructions on their webpage. Students can sign up for emergency text message alerts at plus.hope.edu.

Inclement Weather

Campus Safety sends emergency notification texts, including notices of weather-related closures, via the HOPE ALERT system. A decision to close campus offices and cancel classes is typically announced before 6:30 AM. More information regarding inclement weather notifications can be found on Campus Safety’s webpage.

Academic Assistance Statement

The Academic Success Center (ASC) offers all students various free services (e.g., tutoring, testing strategies, time management resources). The ASC is located in Van Zoeren Hall–immediately adjacent to the Van Wylen Library second-floor entrance. To contact the ASC send an email to asc@hope.edu or call 616-395-7830.

Counseling and Psychological Services (CAPS)

Students may experience stressors that can impact both their academic experience and their personal well-being. These may include academic pressures, relationship challenges, alcohol or other drugs, financial concerns, identity development, body image, etc.

If you are experiencing similar concerns, we encourage you to seek support. Hope College Counseling and Psychological Services (CAPS) is a free and confidential resource. Call 616-395-7945, or visit the top floor of the Bultman Student Center to find the right support for you.

If the source of your stressors is academic, please contact me or academic advising to find solutions together.

Disclaimer

This syllabus is subject to change. If changes occur, students will be notified in class or through an email or Moodle announcement.