Plan ahead for courses where students have earned lower grades.
Lowest historical GPA first. At least 100 letter grades over the five years through the
selected term. Grades reflect past outcomes, not workload or a guaranteed result.
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29 courses
Ranked courses have at least 100 recorded letter grades.
Design of Machine Elements covers analysis and design of machine components, focusing on loads, stresses, fatigue, material selection, and power transmission systems like gearing and bearings.
One student found the course covered a wide range of difficult material that was hard to synthesize, noting there was always a significant amount of work due.
Dynamic Systems covers mathematical modeling and analysis of dynamic systems with mechanical, thermal, and fluid elements, including time/frequency domain solutions and linearization.
One student rated the course difficulty as low, noting that Prof. Berson was very helpful and made significant efforts to assist students during office hours.
Exams were reported as difficult to finish in time, and the instructor did not curve grades. One student noted that homework formatting took more time than the actual heat transfer problems.
Energy Systems Laboratory covers experimental evaluation and analysis of performance for energy conversion systems including turbines, compressors, refrigerators, and fans.
Past student reviews · Tom Krupenkin, Arganthael Berson
Students reported a large amount of work, including a 15-page report and 45-minute presentation with minimal lecture support. Labs required substantial effort, but one student noted it was hard to get a bad grade on them.
This Thermodynamics course covers the first and second laws, properties of gases and vapors, energy-systems analysis including power and refrigeration cycles, and reacting mixtures.
Students reported a significant workload with three homework assignments per week. These assignments were described as manageable but essential, as exams mirrored the homework problems.
Introduction to Artificial Neural Networks covering theory and applications including MLPs, CNNs, RNNs, SVMs, and genetic algorithms for control, pattern recognition, and object detection.
The course had a huge workload with many homeworks, exercises, and a group project. The first half was very difficult without a strong background in Linear Algebra or Calc 3.
Introductory course covering polymer processing, materials, manufacturing, recycling, ethics, and modeling techniques such as dimensional analysis and simulation.
Exams were described as difficult and distinct from lecture material, with one student finding studying extremely hard due to the disconnect between labs and classes.
Matrix Methods in Machine Learning covers linear algebraic foundations including SVD, regression, and regularization applied to classification, clustering, and neural networks.
The course demanded substantial effort outside of class time, as classwork alone did not provide a deep feel for the code or mechanics. One student suggested that mastering Linux and ROS before enrolling would have made the material easier to manage.
Introduction to mechatronics covering DC/AC circuit analysis, active/passive linear circuit design, digital logic, and programming for embedded microcontrollers with lab exercises.
The course involved 3–5 reading assignments per week, and students reported spending significantly more time outside class preparing for exams than the required credit hours.
Engineering Measurements and Instrumentation covers modern instrumentation theory, experiment design and execution, and data analysis. Labs focus on hypothesis testing, product evaluation, and control system design.
Undergraduate course teaching simulation of 1D-3D structural and thermal systems using commercial FE software (ANSYS) via GUI and APDL, focusing on model verification and thermal stress effects.
Homework rubrics were unclear, and one student felt graders deducted small amounts of points. Exams required significant time, and practice questions did not match the midterm difficulty.
Applications of conduction, convection, and thermal-radiation principles to combined-mode problems; analytical and numerical techniques; heat-exchanger design; thermal stresses.
Design and Analysis of Manufacturing Systems covers techniques for designing, analyzing, operating, and controlling modern manufacturing systems through case studies using industry data.
Engineering Design with Polymers covers implications for plastics part design of polymer classification, structure, melt rheology, mixing, blends, anisotropy, solidification, mechanical behavior, and failure.
Homeworks and tests were described as not very hard and straightforward. Students noted that lectures could be watched at 2x speed due to the pacing, and class notes were useful because they could be used on exams.
Introduces metal manufacturing processes, design for manufacturability, automation, control, metrology, and engineering economics for cost determination.
Introduction to geometric description and modeling of mechanical form, components, and assemblies using CAD systems, covering descriptive geometry, engineering drawing, and GDT.
Students reported that the CAD modeling aspect was easy, though the final project was decently time-intensive. The specific workload for the project varied depending on the dynamics of the student's group.
Overview of experimental and modeling techniques for human movement, covering motion capture, force plates, musculoskeletal modeling, inverse dynamics, and forward dynamic simulation.
Advanced topics of special interest in Mechanical Engineering, including vibrations, balancing, lubrication, wear, manufacturing, automation, and energy systems.
The course was described as challenging due to a dense syllabus packed with complex mathematics. While some students found the midterm impossibly hard, others noted that the math was manageable with extra effort outside of class.
A semester-long project course where students redesign and fabricate a Stirling Engine, applying design, manufacturing, and prototype evaluation principles.