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

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

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: 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.

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.

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.

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.

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.