Low Code/No Code AI 

May 28-30, 2024 

11:00 am-4:00 pm EST 

1:00 pm-4:00 pm EST 

1:00 pm-5:00 pm EST 

Facilitator: Gauthier Vasseur | Alliance for Inclusive AI

Seats: 60 

Join Gauthier Vasseur, Executive Director of the Fisher Center for Business Analytics at the University of California, and President/Co-Founder of Alliance for Inclusive AI, for an unparalleled workshop experience!

Designed through Berkeley research and global business expertise, this workshop was born in Silicon Valley and forged by engagements with top-tier organizations worldwide. It's a fusion of cutting-edge content, bleeding-edge topics, and actionable insights.

Experience a holistic dive into analytics covering data management, solution architecture, lean process design, and leadership transformation. Gain insights that seamlessly integrate into your organization's complex ecosystem.

Day 1: Pre-training Session & No Code Analytics 

Day 2: No-Code AI 

Day 3: Low Code and Natural Language Coding 

APPLICATION IS CLOSED 

Presented by the Central Hub at Clark Atlanta University 

Title:  Social Science with R Studio/Posit

Dates: July 24-25

Time: 9:30 am-4:30 pm EST

Available Seats: All seats have been filled at this time. 

Instructor: Lyrric Jackson, Adjunct Professor of Dance, Spelman College; Certified Data Carpentries Instructor - LinkedIn

Lyrric is an American multidisciplinary artist, educator, and data scientist. She received her Bachelors in Drama/Dance Concentration from Spelman College and holds a Masters in Arts Administration and a MFA in LXFM from the Savannah College of Art and Design. She is a Professor of Dance Performance and Choregraphy at Spelman College, an AUCC Data Science Initiative Faculty Affiliate, a Spelman Faculty CODE Scholar, a Certified Data Carpentries Instructor, and a Sloan Data Science Faculty Fellow. Her work extends to local and global arts and educational institutions, including Lyrric Jackson Dance, Brenau University, Emory University, and Mashirika Performing Arts in Kigali, Rwanda. 

Description: This workshop uses a tabular interview dataset from the SAFI Teaching Database and teaches data cleaning, management, analysis and visualization. There are no prerequisites, and the materials assume no prior knowledge about the tools. We use a single dataset throughout the workshop to model the data management and analysis workflow that a researcher would use.

Hosted by the NDSA Central Hub - Clark Atlanta University

Title: Demystifying Deep Learning

Dates: July 20-21

Time: 9:30 AM-4:30 PM

Location: Virtual via Zoom 

Available Seats: All seats have been filled at this time. 

Instructor: Dr. Antonio Moretti, Faculty Fellow, Computer Science Department, Barnard College - Website

Description: This two-day virtual Zoom workshop provides a comprehensive introduction to deep learning for beginners. Some exposure to Python, multivariate calculus, and linear algebra would be helpful. The first half of the workshop will focus on the theory of deep learning including forward and backpropagation, convolutional neural networks, sequence models, transformers, and deep generative models. The second half will serve as a tutorial on automatic differentiation where we use the Python libraries Tensorflow and Pytorch to train and deploy a model on the cloud. All disciplines are welcome. Participants will be able to train and deploy a deep learning model by the workshop's end.

Deep learning refers to a family of models based on artificial neural networks that have recently produced breakthroughs in our ability to analyze images, videos, sound and text. Facial recognition, voice search, medical imaging and self-driving cars are all examples of technologies that are powered by deep learning. This workshop will provide a clear and concise introduction to the theory and practice of deep learning including forward and backpropagation, convolutional neural networks, sequence models, transformers, and deep generative models. A tutorial on automatic differentiation will also be covered where we use the Python libraries Tensorflow and Pytorch to train and deploy a model on the cloud.

Topics include:
- Forward and backpropagation
- Convolutional neural networks
- Sequence models (RNNs and LSTMs)
- Transformers
- Deep generative models
- Automatic differentiation
- Tensorflow and/or Pytorch- Model Deployment

Hosted by the NDSA Central Hub - Clark Atlanta University

Starting Cloud-Based Research on NHLBI BioData Catalyst® (BDC)

Dates:  July 13-14, 2023

Time: 11:00 am to 4:00 pm EST

Location: Virtual via Zoom

Available Seats: 60

Instructors:

• Emily Hughes, Bioinformatics Systems Analyst, BDC Powered by PIC-SURE, Harvard Medical School - LinkedIn

• Dave Roberson, Community Engagement Manager, BDC Powered by Seven Bridges, Velsera - LinkedIn

• Kat Thayer, Senior Project Manager, BDC Powered by Terra, Broad Institute - LinkedIn

Description: NHLBI BioData Catalyst® (BDC) is a cloud-based ecosystem that offers researchers data, analytical tools, applications, and workflows in secure workspaces. It is a community where researchers can find, access, share, store, and analyze heart, lung, blood, and sleep data resources. And it is one of NHLBI’s data repositories, where researchers share scientific data from NHLBI-funded research so they and others can reproduce findings and reuse data to advance science. By increasing access to NHLBI data and innovative analytic capabilities, BDC accelerates reproducible biomedical research to drive scientific advances that can help prevent, diagnose, and treat heart, lung, blood, and sleep disorders.

The workshop is intended for both researchers and faculty who may want to use NHLBI resources in their courses. It is recommended to have an eRA Commons ID, although it is not required. The session will have both lecture and interactive, hands-on demos: an overview of BDC with a focus on setting up an analysis on the ecosystem, including identifying data of interest, identifying relevant data analysis workflows, estimating cloud costs, and data access protocols. After completing the workshop, students can request $500 in free pilot credits to continue practicing analyses or to begin testing new analyses and will have access to on-demand support and additional training opportunities from BDC. 

Registration Closed

Hosted by the NDSA Central Hub - Clark Atlanta University

Title: Navigating the Data Science Landscape: Exploring the What, Why, and How of Data Science

Dates: July 17-18

Time: 9:30 am-4:30 pm EST
Available Seats: All seats have been filled at this time. 

Instructor: Yvonne Phillips, Adjunct Professor of Computer Science, Morehouse College; Data Science/Predictive Analytics Consultant, Trainer, Speaker - LinkedIn

Description:  The workshop aims to empower participants with a solid foundation in data science by introducing key concepts, terminologies, tools, and techniques. Participants will gain the knowledge and confidence to embark on their journey as data scientists. This workshop serves as a valuable stepping stone for individuals seeking to leverage data-driven insights in their professional careers and provides the necessary resources to support classroom instruction, research efforts, and practical applications of data science. 

Hosted by the NDSA Central Hub - Clark Atlanta University

Unlock the Power of Python in Your Classroom: A Workshop for HBCU Faculty and Staff

May 20-21, 2024 

10:00 am-2:00 pm EST 

Facilitator: Nelson Lemieux | Seven Star Academy Inc 

Seats: 40 

Join us for an engaging and practical Python workshop tailored specifically for college faculty and staff across all disciplines.

This workshop aims to empower you with the essential Python skills to seamlessly integrate coding lessons and assignments into your courses, enhancing the learning experience for your students.

Designed for beginners and intermediate learners, this immersive workshop will cover:

-Python fundamentals: variables, data types, operators, and control flow

Advanced topics: functions, modules, data structures, and practical applications

By the end of the workshop, you'll gain:

- Confidence and skills to tackle real-world coding challenges using Python

- The ability to infuse Python into your curriculum, enriching your teaching and your student's learning experience

Python is a versatile language that can open doors to endless opportunities. Bring your curiosity and enthusiasm to learn, and let's explore the world of Python together!

APPLICATION IS CLOSED 

Presented by the Northeastern Hub at Howard University. 

Title: Intermediate Tableau: Empowering Educators to Lead the Next Generation with Data. 

Dates: February 26-28, 2024 

Time: 1:00 pm-5:00 pm EST
Available Seats: 20

Instructors: Jessica Lyons, Sekou Tyler, and Chantilly Juggernaut.   

Description: Join us for this intermediate Tableau workshop where we will take a comprehensive look at Tableau's capabilities, including blending and joining data sets, and curating dynamic presentations using Tableau and Tableau Prep. This hands-on experience will empower educators to harness the full potential of Tableau, enabling them to teach their students how to make informed decisions, tell compelling data-driven stories, and build valuable data skills for the future. Don't miss this opportunity to become a data champion in your classroom!

APPLICATION IS CLOSED.

Hosted by the NDSA Northeastern Hub at Howard University.

Title: Intro to Tableau

Dates: January 8-10, 2024

Time: 9:00 am-1:00 pm EST
Available Seats: 40

Instructor: Dr. Mary Dunaway (Morgan State University) | Chantilly Jaggernauth (Founder & CEO, Millennials and Data) | Sekou Tyler | Lery Dujour | Ayodeji Omokehinde | Travis McGarr | Dr. Jason Davidson (Butler University) 

Description:  Are you ready to level up your data skills and transform your classroom experience? The National Data Science Alliance presents an unparalleled opportunity for educators across all fields and skill levels. This impactful workshop is not just a learning journey but a catalyst for change, aimed at mitigating the data skills gap among our future leaders.  Phase 1 (Introduction to Tableau) is your starting point: Dive into Tableau from the ground up, whether you're a complete beginner or seeking a refresher. Learn the basics and lay a solid foundation for your Tableau journey. 

Hosted by the NDSA Northeastern Hub at Howard University.

RStudio for Social Scientists 

June 17-18, 2024 

9:00 am-2:00 pm EST 

Facilitator: Lyrric Jackson | Spelman College 

Seats: 40 

Join us for an engaging and immersive workshop that will equip you with the essential knowledge and hands-on experience to effectively utilize RStudio!

This two-day virtual workshop introduces R, designed for participants with no programming experience but open to all skill levels. Learners will start with basic information about R syntax, and the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. All disciplines are welcome. Participants will be able to create data visualizations, build complex and customized plots from data in a data frame, and modify the aesthetics of an existing ggplot plot by the workshop’s end.

Topics include:

• Defining objects, assigning values, and naming objects

• Subsetting values form data frames

• Examining and changing data formats

• Data wrangling with dplyr

• Splitting dataframes

• Export a dataframe to a csv file

• Set universal plot settings.

Bring your curiosity and enthusiasm to learn, and let's explore RStudio together!

APPLICATION CLOSED

Hosted by the NSF NDSA Northeastern Hub at Howard University

Workshop on Geospatial Data Science with R 

Dates:  July 24-25, 2024 

Time:  9:00 am to 1:00 pm EST

Location: Virtual via Zoom

Instructor: Dr. Oyebade Oyerinde, Graduate Education Interim Dean and Associate Professor of Public Administration, Clark Atlanta University 

Description

This Carpentries workshop on Geospatial Data Science with R gets learners to a fairly advanced stage of creating geospatial plots (i.e., maps of data distributions) but does not cover data organization or cleaning. It starts out with a short introduction to essential geospatial concepts and a shortened version of our core R lesson before progressing into working with specialized geospatial packages in R. 

APPLICATION IS CLOSED 

Hosted by the NDSA Southeastern Hub at Clark Atlanta University.

R for Reproducible Scientific Analysis 

Dates:  July 11-12, 2024 

Time:  9:00 am to 1:00 pm EST

Location: Virtual via Zoom

Instructor: Lyrric Jackson, Lecturer in the Department of Dance Performance and Choreography at Spelman College and Certified Carpentries Instructor 

Description

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. 

APPLICATION IS CLOSED 

Hosted by the NDSA Southeastern Hub at Clark Atlanta University.

Navigating the Data Science Landscape: The What, Why, and How? 

Dates:  February 17th and February 24th

Time:10:00 am to 3:00 pm EST

Location: Virtual via Zoom

Available Seats: 20

Instructor: Yvonne Phillips, Adjunct Professor of Computer Science, Morehouse College; Data Science/Predictive Analytics Consultant, Trainer, Speaker - LinkedIn

Description

FEBRUARY 17 TH: Navigating the Data Science Landscape: The What, Why, and How?  

• Overview of data science and data analytics concepts 

• Understanding the data science workflow and project lifecycle 

• Learn Big data characteristics. 

• Discuss the ability to translate the business problem into an analytic problem. 

•  Provide specific examples of how those techniques are being used to deliver tremendous value across various areas. 

FEBRUARY 24 TH: Basics of R Programming 

•  Explore R language fundamentals, including basic syntax, variables, and data types and structures. 

•  Learn the basics of data ingestion and selection. 

APPLICATION IS CLOSED 

Hosted by the NDSA Southeastern Hub at Clark Atlanta University.

This two-day virtual workshop (delivered via Zoom) will cover the fundamentals of using Tableau, Tableau Desktop, and Tableau Public. We will provide a hands-on and interactive introduction to the analytics platform.

Participants will learn:

• The basic features of the interface.

• How to add and connect to data

• How to work with the data to create charts and tables.

• How to create worksheets, and dashboards.

• Visualization best practices (including how to choose a chart type).

Data sets will be provided, and participants will create their workbooks and dashboards. After the session, participants will share their data visualizations via Tableau Public. No prior experience is required; however, participants are required to complete pre-workshop prep activities.

APPLICATION IS CLOSED 

Presented by the Southcentral Hub at Fisk University. 

Exploratory Data Analysis (EDA) & Data Visualization 

Dates:  March 21-22

Time: 9:00 am to 5:00 pm CST

Location: Virtual via Zoom

Available Seats: 20

Instructor: Yvonne Phillips, Adjunct Professor of Computer Science, Morehouse College; Data Science/Predictive Analytics Consultant, Trainer, Speaker - LinkedIn

Description: Embark on an immersive journey of Exploratory Data Analysis (EDA) and Visualization through our workshop, meticulously designed to offer participants a comprehensive understanding of foundational concepts and hands-on skills in data exploration and visualization. 

• Gain insights into the significance of data cleaning, integration, and transformation, laying the groundwork for robust data analysis.

• Work with essential functions for data manipulation, with a specific focus on mastering the capabilities of the dplyr package.

• Explore the power of data visualization and learn various important functions to effectively present and manipulate data using visualization techniques.

• Understand the approach and significance of EDA in the realm of data science, setting the stage for comprehensive data exploration.

• Delve into methods for summarizing and exploring data, equipping participants with tools to derive meaningful insights.

• Apply fundamental tools, including plots, graphs, and summary statistics, to conduct effective Exploratory Data Analysis.

• Master the art of creating compelling data visualizations using the ggplot2 package, enhancing the interpretability of complex datasets.

APPLICATION IS CLOSED 

Hosted by the NDSA Southcentral Hub at Fisk University.

Navigating the Data Science Landscape: The What, Why, and How? 

Dates:  January 11-12

Time: 9:00 am to 5:00 pm EST

Location: Virtual via Zoom

Available Seats: 20

Instructor: Yvonne Phillips, Adjunct Professor of Computer Science, Morehouse College; Data Science/Predictive Analytics Consultant, Trainer, Speaker - LinkedIn

Description: The first tier of the academy consists of courses that will introduce the data science ecosystem. These courses provide participants with an overview of the main characteristics of R and demonstrate R’s versatility in working with data objects. The student will work through the steps of a data science project. No prior knowledge of data science or coding is needed.

Hosted by the NDSA Southcentral Hub at Fisk University.