DataedX
Advancing data science capabilities
for the everyday professional
Building data equity skills for an inclusive workplace
About
Data science has emerged as a separate interdisciplinary field. It is regularly applied in the workplace; in fact, many of you may be data science practitioners by proxy – having to process and interpret data without a formal data related background. In order to stay competitive in the tech space, professionals need to expand their understanding of data science and apply these practices to real-world problems. We center data equity in our trainings and events to help organizations, teams and individuals be more inclusive with their data.
Our Offerings
For Groups & Teams
DataedX crafts customized webinars, fireside chats and workshops for various groups. Whether an informative or interactive session, we prioritize delivering content applicable to your group.
Black Women
in Data
BWD center Black women's point-of-view in all spaces where data lives, offer opportunities to expand data skills, communicate issues and recommend advancements.
WHAT PEOPLE SAY
— Janeya Griffin, Founder and CEO of The Commercializer
“Just finished a bootcamp to learn about Data Science for us by us. Y'all Black Women are Amazing! I love Y'all! #datascienceexecutives”
DataedX's Resource Picks
 Getting Started in Data Science by Ayodele Odubela |  Race After Technology: Abolitionist Tools for the New Jim Code by Ruha Benjamin |  Algorithms of Oppression How Search Engines Reinforce Racism by Safiya Umoja Noble |  Bite-Size Python: An Introduction to Python Programming by April Speight |
|---|---|---|---|
 Career Rehab by Kanika Tolver |  Shifting The Double Lives of Black Women in America by Charisse Jones and Kumea Shorter-Gooden |  Advanced Analytics in Power BI with R and Python Ingesting, Transforming, Visualizing by Ryan Wade |  Transfer Learning for Natural Learning Processing by Paul Azunre |
 Bayes Rules! An Introduction to Bayesian Modeling with R by Alicia A. Johnson, Miles Ott, Mine Dogucu |  Design Justice: Community-Led Practices to Build the Worlds We Need by Sasha Costanza-Chock |  An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani |  Trust in Machine Learning by Kush Varshney |
 Deep Learning for Beginners by Dr. Pablo Rivas |  Data Ethics Framework by UK Government |  164 Data Science Interview Questions & Answers by 365DataScience |  Weapons of Math Destruction: How Big Data increases inequality and threatens democracy by Cathy O'Neil |
 Who Gets What — and Why: The New Economics of Matchmaking and Market Design by Alvin E. Roth |  Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor by Virginia Eubanks |
Brandeis H Marshall
co-founder, ceo
With 15+ years as a computer science scholar and educator, Brandeis is a skilled explainer who has a knack of making difficult concepts easier to understand, regardless of a person's educational background. She shares the racial, gender and socioeconomic impact of data in technology.
Susan R Geier
co-founder, coo
Susan's first career in small business management spanned 15+ years. She also has 10 years experience in program development, evaluation, and management. Her work focuses on adult learning, career management, and enhancing educational outreach programs.
