Jonathan Bates

ML Working Group (Spring 2026)

A small, selective, in-person ML working group focused on hands-on deep learning, mentorship, and shipping a real project. This is not a course, not a bootcamp, and not for beginners.

What this is

Over six weekly 2-hour sessions, we will work through a realistic customer support ticket triage task using modern NLP models. Participants will train, evaluate, and deploy a model under real constraints, and leave with a portfolio-ready GitHub repository they fully understand.

This is mentorship-first and intentionally small to preserve depth.

Who this is for

  • MS students, recent graduates, or early-career professionals
  • Prior ML coursework or equivalent experience (e.g., DASC 41103 level)
  • Comfortable with Python and basic ML concepts
  • Able to attend in person in Fayetteville

If you are looking for an introduction to ML, a certificate, or lecture-style teaching, this is not a fit.

Format

  • 6 sessions, Thursdays 6–8pm, in March and April
  • In person (Fayetteville)
  • Small cohort (target: 6–10 participants)
  • Independent work between sessions
  • Optional donation after the first session

What you’ll build

  • A text classification model for customer ticket triage
  • Explicit training and evaluation (no black-box pipelines)
  • Loss curves, metrics, and error analysis
  • A simple HTTP inference endpoint
  • A clean, reproducible GitHub repo you can explain and defend

About the facilitator

Jonathan Bates is an independent ML practitioner with prior experience as a lecturer and research scientist in AI, followed by senior industry roles. He is currently working on independent projects and writing, as well as mentorship.

Apply

This working group is selective and requires an application.

👉 Apply Here

Please apply only if you can commit to attending all sessions in person.

FAQ

Is this a class or for credit? No. This is an independent, non-credit working group.

Is this beginner-friendly? No. Participants are expected to already understand basic ML concepts.

Is there a cost? There is no fixed cost. Optional donation after the first session.

Do I need a powerful machine or GPU? No. All work will be CPU-friendly.

What will I leave with? A real ML project, mentorship, and a strong portfolio artifact.

Questions?

If you’re unsure whether this is a fit, feel free to reach out after reviewing the application requirements.