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MLME: an open-access, project-based AI curriculum for thermal engineering totaling 39.1 hours with four core projects and three optional projects

Design · All designs
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Description

The Machine Learning for Mechanical Engineers (MLME) course at UARK integrates AI into thermal engineering for ME students, distinct from computer-science AI courses by focusing on selection and implementation of AI algorithms for thermal problems. The article states the course is "organized into a timeline format ... totaling 39.1 hours, and covers various topics such as linear regression, multilayer perceptron (MLP), convolutional neural networks (CNN), and time series analysis." Four assignment projects cover heat flux prediction (MLP, GPR), pre-/post-CHF image classification (CNN), unsupervised PCA/SVD clustering, and RNN time-series prediction of vapor fraction; three extra projects and student-proposed projects serve as final-exam options. Syllabus, data, and code are released in open-access repositories.

Design Implications

Context

Requirements

  • Preferred entry requirements are one semester of calculus, linear algebra fundamentals, basic probability/statistics, familiarity with MATLAB or Python, and at least one thermal sciences course; high-school level mathematics and physics is the minimal prerequisite because skills are taught within the course

Constraints

Target Learners

  • mechanical engineering undergraduate and graduate students

Learning Goals

  • develop, train, and test ML models using Python (TensorFlow) and MATLAB
  • apply ML to thermal engineering problems such as boiling monitoring, diagnosis, and prediction
  • NACE professional competencies including critical thinking, communication, teamwork, technology, leadership, and professionalism

Claims

  • Worked Examples Reduced Grade Variance Mlme [+M]

Examples

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Key Sources

  • Changgen Li, Han Hu, Christy Dunlap, Nathaniel House, and Jonathan Wai. (2025). Giving Mechanical Engineers Intelligent Tools: A Project-Based AI Education Curriculum in Thermal Engineering. https://github.com/hanhuark/machine-learning-for-engineers
Page metadata
Field Value
type design
id mlme-course-thermal-ai-curriculum
title MLME: an open-access, project-based AI curriculum for thermal engineering totaling 39.1 hours with four core projects and three optional projects
description The Machine Learning for Mechanical Engineers (MLME) course at UARK integrates AI into thermal engineering for ME students, distinct from computer-science AI courses by focusing on selection and implementation of AI a...
status review
generated by process:settle-candidates on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — changgen-li-2025

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