The Atlanta University Center (AUC) Data Science Initiative invites AUC faculty, staff, and graduate students to participate in interactive, virtual data science workshops. Topics are chosen to upskill and expand knowledge in various areas of data science, coding, data manipulation, machine learning, AI, and analytics. We offer a variety of workshops that target those from across disciplines. The diverse schedules aim to provide opportunities to engage in data science. Participants who successfully complete a summer workshop and its deliverables will be invited to participate in upcoming symposiums and other events.

How to Apply

Eligibility Information
Applicants must be faculty, staff, or graduate students in the AUC, have a working laptop/computer, and access to the internet.


  • Preference is given to those who apply by April 17, 2023
  • Deadline to apply is May 1, 2023  
  • Notifications will be sent by May 10, 2023  


Accepted participants agree to:

  • Attend all days and sessions.
  • Be ready to engage, focus on the task at hand, and not participate in other activities during the workshop.
  • Complete a 2-page report on how the information learned can be used in an upcoming course or research project and is due upon completion of the workshop.
  • Participate in pre- and post-surveys.

Apply at: https://aucdatascience.smapply.io/prog/2023_summer_workshops

  • You must complete a new application for each workshop you are interested in attending. 
  • Remember to complete, SIGN & DATE your W9.

Workshop Descriptions

Teaching Data and the African Diaspora (May 23-24, Tues/Wed; 9:30 am-4:30 pm ET)

This two-day Zoom workshop will prepare AUC faculty to teach a section of “Data & the African Diaspora” during the Fall 2023 semester to AUC undergraduate students. 

SAS – Introduction to Data Science Statistical Methods (May 31, Wed; 9:30 am-4:30 pm ET)

This workshop provides an overview of the statistical methods used by data scientists, with an emphasis on their applicability to business problems. As such, software is not emphasized and mathematical details are kept to a minimum. The workshop starts with how to identify the need for feature engineering – such as sampling, variable transformations, imputation, and variable selection. We then describe applications of supervised models such as decision trees, neural networks, support vector machines, factorization machines, and logistic regression. We continue the discussion by examining the usefulness of unsupervised models, such as clustering, text mining, network analysis, and path analysis, and finish by exploring model assessment and deployment, such as visualization and monitoring. Class size: 50 participants. Stipend: A stipend of $250 will be paid upon completion and submission of the deliverables.

Intermediate R Academy (June 1-2 & 5-6, ThFMT; 9:00 am-4:00 pm ET)

The Intermediate R Academy/R2 is for those who completed the Beginner R Academy or have previous R knowledge. Participants should come in with knowledge of how to write scripts and code in R for research in their discipline or teach a module using R. This Intermediate class will cover these topics: Intro to machine learning, linear regression analysis, cluster analysis, and classification using random forests. Class size: 20 participants.  Stipend: A stipend of $1000 will be paid upon completion and submission of the deliverables.   

[IN-PERSON] Symposium on the Power of Black Health Equity Conference (June 8, Th; 6:00 pm-9:00 pm; June 9, 9:30 am-4:30 pm ET; Morehouse School of Medicine, Atlanta, GA)

This symposium explores the Power of Data Behind Black Health and how to develop equitable solutions for healthier communities. Participants will engage in multidisciplinary discussions that explore how to advance AI/ML approaches that improve health outcomes and address health disparities, in particular, for those from Black communities. Topics include AI/ML approaches that address health disparities, the impact of cultural insensitivity in AI/ML algorithms and models, and methodologies that promote transparency and mitigate bias in AI/ML algorithms and models. Faculty, staff, and graduate from Minority Serving Institutions (MSIs) and community and corporate professionals in the southeastern region (AL, FL, GA, PR, SC, and VI) are encouraged to attend. This Symposium is co-hosted by the Atlanta University Center (AUC) Data Science Initiative and the AIM-AHEAD Southeast Hub at Morehouse School of Medicine. COVID-19 safety protocols will be observed.  APPLY HERE!

[IN-PERSON] Data-Driven Entrepreneurship with VentureWell (June 13, Tues; 9:30 am-4:30 pm ET)

This in-person workshop will show data is being used by entrepreneurs to make informed decisions and provide innovative insights. Using real-world policy examples, the workshop will provide an overview of the importance of data science-specific data science topics that motivate entrepreneurship. Participants work in groups to apply foundational concepts of data science to a business case study. Then, groups of participants will explore how to work across disciplines to leverage publicly available data to exchange an existing innovation and entrepreneurship policy using basic data science approaches. The participants will then share out their discoveries and reflections. Class size: 50 participants. Stipend: A stipend of $250 will be paid upon completion and submission of the deliverables.

SAS – Why SAS + Academic Resources for Teaching and Learning + Getting Started with SAS Studio: A Point and Click Approach  (June 15, Thurs; 9:30 am-4:30 pm ET)

In this session, we’ll provide an overview of the resources provided in GAP, as well as a tour of SAS software from Base SAS to Enterprise Miner, SAS Visual Analytics, and SAS Model Studio. This is a great session to become familiar with SAS, get a broad overview of its capabilities, and better understand the free software options available for academics. This hands-on workshop shows how one can use the menu-driven tasks and SAS code in SAS Studio to perform common reporting and research tasks, including querying, reporting, and analyzing data. SAS Studio provides a point-and-click, graphical user interface, as well as predefined code that helps you exploit the power of SAS. In this workshop, participants will learn to access data, combine tables, compute new variables, explore data with simple statistics and graphs, and perform sophisticated statistical analyses with SAS Studio. This course does not teach statistical concepts but teaches how to use these tools with SAS Studio. Class size: 50 participants. Stipend: A stipend of $250 will be paid upon completion and submission of the deliverables. 

[IN-PERSON] Introduction to Tableau (June 16, Fri; 8:30 am-5:00 pm ET)

This is a hands-on workshop that will cover the fundamentals of creating visuals using the Tableau Business Intelligence tool. No prior experience is required. Participants will learn 1) the basic features of the interface and how to navigate within the tool; 2) how to import and connect to data; 3) visualization best practices (including how to choose a chart type); and 4) how to create interactive dashboards and stories that can inform. Participants will work in groups and data sets will be provided to give hands-on experience in creating visualizations. At the conclusion of the workshop, participants will have basic skills to navigate within Tableau and will create a Tableau dashboard that will be shared with the workshop participants. Class size: 30 participants. Stipend: A stipend of $250 will be paid upon completion and submission of the deliverables. 

Library Data Analysis Core – The Library Carpentry  (June 20-21, Mon/Tue; 9:30 am-4:30 pm ET)

This workshop provides an introduction to data analysis and good practices, including versioning, cleaning, automation, manipulation, and structured queries. Participants will learn: 1) Introduction to Git, 2) The Unix Shell, 3) OpenRefine, and 4) SQL. There are no prerequisites, and the materials assume no prior knowledge about the tools. The data used in this workshop include bibliographic metadata and text-based data. This workshop teaches how to clean, integrate, modify and visualize metadata in a disciplined way, debug programs systematically, and use tools to communicate data internally and externally. Class size: 20 participants. Stipend: A stipend of $500 will be paid upon completion and submission of the deliverables.  

Plotting @ Programming in Python – The Software Carpentries (June 22-23, Thurs/Fri; 9:30 am-4:30 pm ET)

This workshop provides an introduction to programming in Python 3 for people with little or no previous programming experience. It uses plotting as its motivating example. Before the workshop, participants need to understand what files and directories are, what a working directory is, and how to start a Python interpreter. Participants must install Python 3 before the class starts and get the gapminder data before the workshop starts. Instructions on installing Python 3 and the gapminder data will be provided to those confirmed for the workshop. Class size: 20 participants. Stipend: A stipend of $500 will be paid upon completion and submission of the deliverables. 

SAS – Getting Started with SAS Visual Analytics (July 10,  Mon; 9:30 am-4:30 pm ET)

In this course, participants are introduced to SAS Visual Analytics and how it is leveraged to create interactive dashboards. Participants will be shown how to use the visual interface to prepare data, analyze data, and design reports. Topics covered include how to access and investigate data, prepare data for analysis, perform data discovery and analysis, and create interactive reports. Class size: 50 participants. Stipend: A stipend of $250 will be paid upon completion and submission of the deliverables. 

Teaching Reproducible Research – Project TIER (July 20-21 & 24-25, ThFMT; 9:30-1:30 pm ET)

Project TIER (Teaching Integrity in Empirical Research) promotes the integration of principles and practices related to transparency and replicability in the research training of social scientists. This workshop will introduce participants to Project TIER’s principles and practices of integrating reproducible methods into teaching and research. The workshop will feature examples in the R programming language. Participants should already be familiar with R or another statistical scripting language (e.g., Stata, SPSS, SAS, etc.). Participants should also have some experience teaching courses involving applied data analysis and/or supervising data-based student research projects and expect to teach such a course again in the near future. During the workshop, participants will create an output (such as a lab exercise or instructions for a reproducible research project) based on principles they learn in the workshop that they can use in their own teaching in the upcoming academic year. Participants will have the option of a follow-up meeting in the summer of 2023 to discuss their experiences integrating reproducibility into their classes or personal research practices. Class size: 20 participants. Stipend: A stipend of $1000 will be paid upon completion and submission of the deliverables. 

“Data analytics has become the vital skill for business students in today’s environment. Recruiters emphasize it constantly and we are hearing from our alumni and interns returning from the summer that they need to strengthen these skills. It does not matter which area of business you plan to enter; you need to know how to understand and analyze data.”

— Dr. Keith Hollingsworth, Department of Business Administration, Morehouse College