ME 4710 – Foundations in Machine Learning for Engineers

Teaching Assistant for ME 4710 – Foundations in Machine Learning for Engineers at Georgia Tech (Fall 2025), working with Dr. Jarred Fountain.

About the Course

ME 4710 is aimed at mechanical engineering students who need a working understanding of machine learning — not as a black box, but as a set of tools with specific assumptions, failure modes, and appropriate use cases. The course covers statistical modeling, experimental design, feature engineering, algorithm selection, and model evaluation under uncertainty. A recurring theme is knowing when not to apply ML, which is less common in typical ML curricula.

Responsibilities

Designed grading rubrics for weekly programming assignments and graded student submissions with technical feedback covering Python implementation quality, experimental design choices, feature selection rationale, and interpretation of model outputs. Responded to student questions over email on topics including cross-validation, statistical significance, and the practical limits of different algorithm families. Worked with Dr. Fountain to refine assignment specifications as the semester progressed.

Instructor

Dr. Jarred Fountain, School of Mechanical Engineering, Georgia Institute of Technology