Introduction to Machine Learning For Engineering Research (ML4ER)

“Introduction to Machine Learning For Engineering Research” (ML4ER) is a semester long course taught in the Spring and Fall semesters, as well as in a condensed 4-week session over the Summer. It serves as an introduction for anyone interested in participating in research related to informatics for engineering, but is currently lacking some of the technical skills and background to jump directly into participation on a research project. Starting Summer 2024 it will be offered for both undergraduate and graduate students interested in building research skills.  The course content is open to everyone, it is modular, flexible, and free to use. Additionally, it is open to in-person and remote participants both within and outside of UW.

This curriculum provides students an introduction to software tools and the associated technical background to understand their use at an introductory level. Throughout the curriculum, students will work hands-on using Jupyter Notebooks with popular Python libraries such as Scikit-learn, Tensorflow, and Pytorch to generate machine learning models. They will learn key ideas for assessing model performance and decision making skills for how to improve or modify a model.

Summary of Summer 2024 Session Information

Course Discussion Times:
Mon or Tues 4:00pm-5:15pm central time

Location:
Remote Attendance via Zoom

Office hours / help desk: Wed/Thurs 9:30am-11:00am central time via Zoom

Start Date: July 15th
End Date: August 11th

Enrollment: Enrollment is open to both UW-Madison students as well as remote students from other institutions and locations. Please fill out the general Skunkworks Application form and note your interest in the course.

Course Credit: Students enrolled at UW are encouraged to also sign up for course credit through MSE 401 (MSE 803 for graduate students) for 3-credits. This is not required to participate in the course. Note that mse 401 is not open enrollment please reach out to the instructors to get permission to enroll after submitting the above google form.

Summary of Spring 2024 Information

Course Discussion Times:
Mon or Tues 4:00pm-5:15pm central time

Location:
Remote Attendance via Zoom

Office hours / help desk: Wed/Thurs 9:30am-11:00am central time via Zoom

Start Date: Jan. 29th
End Date: May 5th

Enrollment: Enrollment is open to in-person UW students as well as remote students from other institutions and locations. Please fill out the general Skunkworks Application form and note your interest in the course.

Course Credit: Students at UW are encouraged to also sign up for course credit through mse 401 for 2-credits under Dane Morgan’s section. This is not required to participate in the course. Note that mse 401 is not open enrollment please reach out to get permission to enroll.

Summary of Fall 2023 Information

Course Discussion Times:
Mon or Tues 4:00pm-5:15pm central time

Location:
MSE 275 in-person
Remote Attendance via Zoom

Office hours / help desk: Wed/Thurs 9:30am-11:00am central time via Zoom

Start Date: Sept. 18th
End Date: Dec. 8th

Enrollment: Enrollment is open to in-person UW students as well as remote students from other institutions and locations. Please fill out the general Skunkworks Application form and note your interest in the course.

Course Credit: Students at UW are encouraged to also sign up for course credit through mse 401 for 2-credits under Dane Morgan’s section. This is not required to participate in the course. Note that mse 401 is not open enrollment please reach out to get permission to enroll.

Course participants are required to attend one of the discussion times or help-desk times each week as well as periodic community wide activities such as the end of semester meeting. Each week students will be introduced to the core concepts, tools, and activities through prerecorded lectures and an associated activity to be completed each week. The materials are largely based around a set of introductory research modules and professional development activities which are described in more detail in the “Materials” section.

In addition to attending weekly meetings, and completing the weekly activities, the main deliverable that contributes to each students grade (for those receiving course credit) is a weekly slide deck that summarizes the activity completed each week. This set of weekly slide decks, one Final Slide Deck submitted at the end of the semester, and attendance requirements contribute to each student’s grade (again for those receiving credit). For students not receiving course credit, they will also receive a certificate of completion if they meet the same requirements for a passing grade as those formally enrolled.

It is expected that between meetings, work groups, and completion of activities that students will spend ~6 hours of time on work related to their participation in the course. This typically corresponds to approximately a 2 credit hour course if receiving credit for an independent study course.

Benjamin Afflerbach
Materials Science and Engineering
bafflerbach@wisc.edu

Specific Syllabi are listed here for recent semesters:

Spring 2024

Fall 2023

Spring 2023

Fall 2022

Spring 2022

Fall 2021

The main materials used throughout the course can be found here

To enroll for the Spring 2024 semester please reach out to the instructor and we will be in touch!

For students participating through the University of Wisconsin – Madison, you are able to receive course credit through MSE 401. This course is an independent study course that requires specific permission to enroll. Please reach out to the instructors if you would like to receive credit.

Students from other institutions should consult with relevant personnel at their institution about possible credits.  We will provide final materials and suggested grades for all participants.

  1. How much programming, or coding background is required to participate?
    We do not require students to come in with any specific programming experience. There will be significant time spend however running existing python code through Jupyter Notebooks, so some basic familiarity with python may help with understanding the concepts that are being demonstrated by running the existing python code. There will also be activities where students are tasked with making single line replacements to existing code to change settings in the code.
  2. Does participation in the ML4ER course impact future acceptance to Informatics Skunkworks research projects?
    Yes we prioritize students who have completed the ML4ER course when considering applications for future research.