Syllabus

CMSE 802: Methods in Computational Modeling - Fall 2026

1. Date, Time and Location

Please see the course D2L page or MSU course catalog for class meeting times and locations.

2. Instructional team & resources

3. Is this the right course for you?

This course will use the Python programming language extensively and you should have a programming skill level similar to students finishing courses such as CMSE 201, CMSE 801, or equivalent. You should be familiar with defining variables, basic mathematical operations, control loops, conditional and logical statements, input/output, and error handling using Python. If not, you will not have sufficient background and should take CMSE 801 instead.

On the other end of the spectrum, this course aims to introduce a number of basic concepts in computational modeling. It is mostly a survey course of commonly used approaches, with little time to explore each approach in depth. If you already have the background in most of the topics introduced below, this course might not be at your level. You may consider special topic courses offered by CMSE, CSE, STT, or MTH.

4. Synopsis

Course goal and teaching philosophy

CMSE 802 is a research software course for graduate students who need to build software that advances real research goals. The course is designed as a software-writing seminar: you make steady progress on your own research-aligned project while practicing professional engineering habits.

Our quality framework is:

• Safe
• Portable
• Reproducible
• Robust
• Literate

These five dimensions are used throughout class activities, peer review, project checkpoints, and final evaluation.

AI in this course

AI-assisted development is encouraged, but outputs must be validated. Treat AI as a collaborator to evaluate, not an oracle to obey.

When you use AI tools, you are expected to:

• verify claims with tests, reasoning, or direct checks
• document what AI contributed and what you changed
• cite substantial AI-generated content when required by assignment instructions

Learning objectives

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

• Build research software that is usable beyond one-off scripts.
• Apply sustainable software engineering workflows to your own research code.
• Use AI assistants responsibly with explicit validation and trust calibration.
• Explain how Analytical, Physical, and Data-Driven components combine in models connected to your research questions.
• Deliver a final software project with clear evidence of software quality and reproducibility.

Primary topics

• Research software engineering workflows (version control, modular design, testing, documentation, review).
• Conceptual modeling fluency using Analytical, Physical, and Data-Driven components as a working convention to guide discussion and design choices.
• Reproducibility practices (environment strategy, run instructions, evidence capture).
• Collaborative development and handoff quality.

5. Course format

How class time is used

Most class meetings combine short framing lectures with guided project work, technical studios, and peer feedback. The emphasis is practical: each week should produce visible progress in your repository.

Course components and assessment

In-class work and participation: Active engagement in class coding, team collaboration, and discussions.

Project checkpoints: Short, evidence-based submissions throughout the semester. Typical evidence includes repository links, tests, reproducibility notes, and concise reflections.

Peer reproducibility review: Structured review using the course SPRRL rubric/checklists. You will both review peers and respond to feedback on your own project.

Final project and presentation: A research-aligned software artifact plus a final presentation that explains both scientific value and engineering quality.

Midterm exam: This course does not include a midterm exam.

Grade information

Regular participation is important for success in this course. We recognize that students balance many responsibilities, so the expectation is not perfect attendance but a good faith effort to attend, engage, and communicate. Students are asked to complete the daily check-in form before each class meeting. The purpose of the check-in is to help build trust, accountability, and professional communication. If you are unable to attend or expect to be late, use the form to let the instructor know why and, when appropriate, your plan for staying engaged with the course. Attendance, participation, and communication may be considered as part of your participation grade. The form is available at:

Daily Check-in Form

Grade Breakdown

Grading Scale

At the end of the semester, your grade will be calculated using the following scale:

Required materials

• A laptop computer with a reliable internet connection.
• Access to Microsoft Teams and D2L.
• Course software as described in the software setup guide.
• No required textbook. Core materials are course pages, code resources, and in-class activities.

Environment expectations

You will maintain two complementary environment strategies in this course:

• Reproducible environment: exact pins for verification consistency.
• Robust environment: compatibility-oriented constraints for broader installation success.

Both strategies are part of professional research software practice.

6. Course Policies and Expectations

Attendance

Attendance is required. This course depends on in-class project work, feedback, and collaboration.

• Unexcused absences receive zero points for that class day.
• Repeated late arrival or early departure without prior arrangement may be treated as an unexcused absence.
• If you have a legitimate conflict (for example conference travel or interviews), contact the instructor in advance to discuss accommodations.

Communication

Course website and D2L: The course website provides current guides and schedule context. D2L is the official platform for assignment submission and grade-related logistics.

Email: Official course messages are sent to your MSU email account. You are responsible for checking it regularly.

Teams: Teams is the primary channel for course Q&A and peer support. Search for existing answers first, keep discussions professional, and use office hours for complex issues that need extended troubleshooting.

Inclusive classroom behavior

Respectful and responsible behavior is required at all times. Productive class discussion depends on listening, constructive language, and shared professional standards.

Expressions or actions that demean individuals or groups are not acceptable and may lead to removal from class activities and referral to university processes.

Article 2.III.B.4 of the Student Rights and Responsibilities (SRR) for students at Michigan State University states: “The student’s behavior in the classroom shall be conducive to the teaching and learning process for all concerned.” Article 2.III.B.10 of the SRR states that “The student and the faculty share the responsibility for maintaining professional relationships based on mutual trust and civility.” General Student Regulation 5.02 states: “No student shall . . . interfere with the functions and services of the University (for example, but not limited to, classes . . .) such that the function or service is obstructed or disrupted. Students whose conduct adversely affects the learning environment in this classroom may be subject to disciplinary action through the Student Judicial Affairs office.

Accommodations for Students with Disabilities

We are committed to providing equal opportunity for participation in all programs, services and activities. Requests for accommodations by persons with disabilities may be made by contacting the Resource Center for Persons with Disabilities at 517-884-RCPD or on the web at rcpd.msu.edu. Once your eligibility for accommodation has been determined, you will be issued a Verified Individual Services Accommodation (“VISA”) form. Please present this form to the instructor at the start of the term and/or two weeks prior to the accommodation date (test, project, etc.). Requests received after this date may not be honored.

Academic honesty

Intellectual integrity is the foundation of scientific enterprise. In all instances, you must do your own work and give proper credit to all sources that you use in your papers and oral presentations – any instance of submitting another person’s work, ideas, or wording as your own counts as plagiarism. This includes failing to cite any direct quotations in your essays, research paper, class debate, or written presentation. The MSU College of Engineering adheres to the policies of academic honesty as specified in the General Student Regulations 1.0, Protection of Scholarship and Grades, and in the all-University statement on Integrity of Scholarship and Grades, which are included in Spartan Life: Student Handbook and Resource Guide. Students who plagiarize will receive a 0.0 in the course. In addition, University policy requires that any cheating offense, regardless of the magnitude of the infraction or punishment decided upon by the professor, be reported immediately to the dean of the student’s college. (See also the Academic Integrity webpage.)

It is important to note that plagiarism in the context of this course includes, but is not limited to, directly copying another student’s solutions to assignments; copying materials from online sources, textbooks, or other reference materials without citing those references in your source code or documentation or having somebody else do your in-class work or homework on your behalf. Any work that is done in collaboration with other students should state this explicitly and have their names as well as yours listed clearly.

More broadly, we ask that students adhere to the Spartan Code of Honor academic pledge, as written by the Associated Students of Michigan State University (ASMSU):

“As a Spartan, I will strive to uphold values of the highest ethical standard. I will practice honesty in my work, foster honesty in my peers, and take pride in knowing that honor is worth more than grades. I will carry these values beyond my time as a student at Michigan State University, continuing the endeavor to build personal integrity in all that I do.”

Limits to confidentiality

Essays, journals, and other materials submitted for this class are generally considered confidential pursuant to the University’s student record policies. However, students should be aware that University employees, including instructors, may not be able to maintain confidentiality when it conflicts with their responsibility to report certain issues to protect the health and safety of MSU community members and others. As the instructor, I must report the following information to other University offices (including the Department of Police and Public Safety) if you share it with me: suspected child abuse/neglect, even if this maltreatment happened when you were a child, allegations of sexual assault or sexual harassment when they involve MSU students, faculty, or staff, and credible threats of harm to oneself or to others. These reports may trigger contact from a campus official who will want to talk with you about the incident that you have shared. In almost all cases, it will be your decision whether you wish to speak with that individual. If you would like to talk about these events in a more confidential setting you are encouraged to make an appointment with the MSU Counseling Center.

Drops and Adds

Please check MSU Academic Calendar for important date on last day to add, drop, and others. You should immediately make a copy of your amended schedule to verify you have added or dropped this course.

Commercialized Lecture Notes

All lectures, videos and notes provided in this course are copyrighted by the university. Recording of lectures and/or commercialization of other university-provided course materials is not permitted.

Grief Absence Policy

Michigan State University is committed to ensuring that the bereavement process of a student who loses a family member during a semester does not put the student at an academic disadvantage in their classes. If you require a grief absence, you should complete the Grief Absence Request web form no later than one week after knowledge of the circumstance. The instruction team will work with you to make appropriate accommodations so that you are not penalized due to a verified grief absence.