ENR 145: Computational Methods for Physicists and Engineers
Department of Engieering Physics, Coe College | Cedar Rapids, Iowa
Course Description
In modern physics and engineering, computation is essential for planning, modeling, visualization, and analysis. It provides viable means—sometimes the only viable means—to make sense of what is going on.
In this course, we will visit some parts of the 'grand computational world.' By the end of the semester, you will dig deep and build projects using the same tools that professionals use. We are not just learning syntax; we are learning how to solve problems.
Modules Covered:
- Python: General intro to coding, data analysis, visualization, and algos.
- COMSOL: Application of ODE/PDEs, FEA, and CFD.
- MD Simulations: A dive into Molecular Dynamics.
- Final Project: A multi-week project to showcase your new skills.
Digital Survival Skills:
- IDE setup to make you code like a pro.
- Prompt and vibe coding with generative AI.
- Speed up your office work, paperwork, or even your homework with AI assistants.
- GitHub page set-up, since everything needs a GitHub page now.
- Spreadsheet, slide decks, and how to design graphs and illustrations.
Module 0: Numerical Methods (1 week)
Module 1: Codes, Visuals, and Algos (4 weeks)
Module 2: Multiphysics Simulation (3 weeks)
Module 3: Cluster-based MD Simulation (2 weeks)
Module 4: Digital Toolbox (1 week)
Module 5: Final Project (Weeks 13-15)
Course Philosophy
Grading: The Learning Loop
This course uses a mastery-based "learning loop." There is no partial credit. Assignments are evaluated as:
Exemplary
Success
Retry
The goal is to try, make mistakes, reflect, revise, and try again—without penalty for mistakes, as long as you demonstrate growth.
Tokens
You will start with 5 tokens. One token can be spent to extend the deadline by 36 hours or to retry an assignment a second time (a third submission). Ten tokens can be used to waive one assignment while still getting an "S" mark.
AI Policy: "Roller Skates, Not Crutches"
AI tools (like ChatGPT or Copilot) are permitted as long as they support your learning and do not replace your independent thought. All AI-generated content (code or text) must be clearly cited and labeled.
About me
Xiang Li
Email: xili@coe.edu
Office: Peterson Hall 141
Office Hours: Monday and Wednesday 9:30am-12:00pm, Monday and Tuesday 1:00pm-3:00pm
Schedule a Meeting: Book a Time Slot
Class Details
Lecture Sections:
- ENR 145 01: MW 3:00 PM - 4:20 PM
- ENR 145 02: TR 11:00 AM - 12:20 PM