The UArizona Machine Learning Literacy Project

A Free, 1-Day Workshop

Saturday, 8 February 2020

9 am - 4 pm, lunch provided

Location: ENR2 S107

This introductory ML-AI workshop is aimed at upperclass and grad students in non-Computer Science majors.

Attention Upperclass and Grad Students!

Come and learn key Machine Learning-Artificial Intelligence concepts and how they are transforming your major area of study! With the UArizona’s ML-AI experts and the Data Science Institute’s ambassadors to guide you, this free, interactive, 1-day workshop will de-mystify ML-AI concepts for non-Computer Science students. No matter what your major is, employers need and want a 21st century workforce that is ML-AI savvy. All attendees will receive a certificate of participation.

This free workshop is limited to 80 participants.

Applications due January 10, 2019

Applicants selected to attend will be notified by January 17, 2020

Workshop Outcomes:

Learn and understand basic ML concepts through researching numerous scientific examples in your discipline
Understand how ML is being applied and has advanced research in your domain/study area
Gain experience in working collaboratively in inter- and multidisciplinary teams
Research, prepare and deliver effective short presentations to a diverse audience
Learn about other opportunities at UArizona for data science learning and applications
Help build capacity at UArizona to meet workforce requirements in the data revolution era

Agenda

9:00 - 9:20 Welcome & Introductions (Keaton Hamm, Faryad Sahneh)

9:20 - 10:10 Key ML-AI Concepts 101 (Carlos Scheidegger and Meredith Kupinski)

10:10 - 10:50 Finding those needles in the haystack (or how to do a killer literature search) (Jason Dewland)

10:50 - 11:00 Break

11:00 - 11:15 The Mission (not impossible!)

11:15 - 12:30 Break into Teams for researching ML/AI applications in domain areas (based on your major; see Helpers)

Each team chooses its lightning talk subject; Teams research ML/AI applications in their research domain and collect/develop presentation materials

12:30 - 1:30 Lunch provided; continue to work on your team project/talk

1:30-2:15 Teams choose presenter(s); prepare and practice a 3-minute lightning talk (5 slides max)

2:15 - 2:30 Break (put your presentation on a USB/thumb drive and bring to presentation PC)

2:30 -4:00 Lightning talks (each 3-min max)

4:00 Wrap up and more ML-AI Learning Opportunities (Keaton and Faryad)

This workshop is made possible by support from the UA Data Science Institute, TRIPODS project, and CyVerse.

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