UArizona Data Lab

 

UArizona DataLab

Empowering Innovation

The DataLab, run by UArizona's Data Science Institute and ICDI, is an AI/ML-inspired makerspace. The lab offers workshops, tools, and resources to provide students, faculty, and industry partners with hands-on experience, using deep learning methods for analyzing large multi-modal datasets and developing novel AI/ML-powered applications.

 

DataLab Workshops

This hybrid workshop provides graduate students the necessary skills for effective data management analysis techniques in data engineering.

Students will learn advanced database management systems, ETL (Extract, Transform, Load) processes, and big data technologies, ensuring a comprehensive understanding of the data engineering landscape. 

When: Every Monday from 2-3 pm 

Where: Weaver Science and Engineering Library Rm 212. You can also join virtually through this Zoom link.

More information

 

Discover the latest trends in geospatial data science where open tools, cloud technologies, and the proliferation of sensor data are innovating earth observation and environmental monitoring. 

In this immersive hands-on workshop students will work with essential geospatial python libraries, learn about cloud-native formats and receive mentorships in open-source drone imagery analysis. 

The series is open to all University of Arizona personnel and is tailored for graduate students, postdocs, and early career faculty looking to expand their geospatial skills.

When: Every Tuesday from 2-3 pm

Where: In-person at the Weaver Science and Engineering Library, Rm 212, or join virtually using this Zoom Link.

Workshop content and more details can be found on this Workshop Wiki Page

Register Here

 

In this workshop series graduate students will gain the necessary skills for their Ph.D. research in data science. Sessions cover a variety of topics such as AI tools, statistics, visualization, machine learning, natural language processing, deep learning, prompt engineering and more. 

When: Every Tuesday from 3-4 pm.

Where: Weaver Science and Engineering Library, Rm 212 or virtually through this Zoom link.

Workshop content and more information can be found on this Data Science Essentials Wiki Page

Register Here

 

This workshop series offers essential data science tools for Ph.D. dissertation research. Participants will learn command line, version control, project management, data handling, documentation, and workflow automation. These skills improve data analysis, visualization, and research quality.

Understanding Before Doing Workshop Overview:
If you lead a team, or are part of a team, that works toward common goals and objectives daily – this workshop is for you. This is a comprehensive leadership workshop useful to anyone searching for career advancement strategies and easily applicable leadership-oriented skills. Get a jump start on the new year and gain a fresh, positive perspective on leadership, planning, and project management to help your team succeed in current and future endeavors.

When: Every Wednesday from 1-2 pm.

Where: Sessions will take place at the Weaver Science and Engineering Library, Rm 212. Participants can also join virtually using this Zoom link.

NOTE: The Understanding Before Doing workshops will meet in-person at the BIO5, Thomas W. Keating Bioresearch Building, Room 103 or virtually using this Zoom link.

  • 02/07 - Leadership, Planning, & Project Management Overview

  • 02/14 - Planning Session with Special Guest, Clara Curiel-Lewandrowski, MD 

  • 02/21 - Project Management Session 

Workshop content and more information can be found on this Data Science Tapas Wiki

Register Here

“Mastering Machine Learning: Your Path to Data-Driven Research” covers essential topics in classical machine learning for data analysis and visualization in Ph.D. research. Participants will gain hands-on experience with popular machine learning libraries and algorithms, enabling them to make informed decisions and conduct advanced data-driven research.

When: Every Thursday from 3-4 pm.

Where: In-person at the Weaver Science and Engineering Library, Rm 212 or virtually through this Zoom link.

Workshop content and more information can be found on this Machine Learning Workshop Wiki.

Register Here

In this series, participants will learn everything about deep learning. From how deep learning works fundamentally through all the possible applications. By the end of this workshop series, participants will be able to build their own ChatGPT. No pre-requisites except Python knowledge is required.

When: Every Thursday from 3-4 pm.

Where: In-person at the Weaver Science and Engineering Library, Rm 212 or virtually through this Zoom link.

Workshop content and more information can be found on this Intro to Deep Learning Wiki

Register Here

Data Lab Activities

Coffee and Code

Coffee & Code

What: Coffee & Code is a place to share ideas, receive and give support and knowledge, connect with other researchers and build a community. Stop by every Wednesday morning. 

Where: Catalyst Cafe at BSRL
When: 8.30AM - 10.30AM, every Wednesday
 

Hacky hour

Hacky Hour

What: Hacking + Happy Hour = HackyHour! Every week, researchers, data scientists, and programmers around campus get together. Some people bring their programming problems to get help from those with more experience. Those without projects come to discuss their research, brainstorm new ideas, try out new technologies, or chit chat about data science!

Where: Snakes & Lattes (University Blvd)
When: 4PM - 7PM, every Thursday

Code Commons

Code Commons

What: Code Commons is a community of practice for people in Tucson working with code and building software. Everyone is welcome to bring their laptop, projects and share ideas. 

Where: CATalyst Data Studio, UA Main Library (map)

When: Wednesdays 2-6 PM

Consultation Services 

To  schedule a consultation, please email the Data Lab Team

Tools
  •  AI applications research software
  • Cloud based analytic tools
  • Data mining & analytics tools
  • Data visualization tools
  • Data protection & validation
Research Topics

Deep Learning

  • Generative AI for Vision: Diffusion Models and GANs
  • Large Language Models
  • NeRF: Neural Radiance Fields
  • Object Detection and Segmentation
  • Vision Transformers - VIT

Machine Learning

  • Federated Learning

Learn More

Resources
  • DL Training Resources
  • Newsletters 
  • Medium Publications
  • Substack
  • Recommend Courses
  • LLMs
  • Machine Learning & Deep Learning
  • More learning Resources

Visit Resources

 

Data Lab Team

Jeff Gillan
Michele Cosi
Carlos Lizárraga
Mithun Paul

Andrew Bennett
Greg Chism
Angela Cruze
Tina L. Johnson
Enrique Noriega
Maliaca Oxnam
Tyson Swetnam

Ankit Pal (GA)
Eric Fingalson (V)
Atharva Goel (HS)
Brenda Huppenthal (GA)
Linda Engelman (U)
Megh Krishnaswamy (GA)
Mario Weiler (U)
Patrick Lohr (V)
Quanwei Lei (U)
*GA=Graduate Assistant, U=Undergrad, V=Volunteer