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A Conversation with Deja Bond: Responsible Data Science

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Join the New Jersey Institute of Technology’s Institute for Data Science for the Spring 2021 Seminar Series bringing together scientists, engineers, and users to develop data-driven technologies to solve real-world problems.

A Conversation with Deja Bond: Responsible Data Science. In May 2020, Deja became the first African American woman to obtain her M.S for NYU

About this Event

Data changes and improves how we work together, mingle, lead research, and administer society. Data/information are gathered on anything, whenever, and wherever. Numerous associations are putting intensely into Big Data advancements and data science has developed as another logical order giving strategies, techniques, and instruments to pick up worth and bits of knowledge from new and existing informational indexes. Data and what we do with it can possibly drastically improve our lives by making new administrations and items, while likewise upgrading their productivity and quality. With each extraordinary improvement, there are a couple of concerns – irresponsible data use. Many data-driven choices might be untrustworthy. Sensitive information might be shared accidentally or mishandled. Data used for machine learning for models reflect existing social predispositions. Which thus makes it hard to receive the rewards of data science. Data science procedures, frameworks, and approaches can be made mindful by design.

Deja Bond is a 24-year-old Philadelphia native. She earned a Bachelor’s of Science in Computer Science at Spelman College in December 2017. She then transitioned into the tech industry as a Software Engineer/Consultant. While working full-time she pursued her Masters of Data Science from the #1 institution in its field, New York University-Center for Data Science. In May 2020, Deja became the first African American woman to obtain her M.S for NYU in Data Science. Now a Product Manager at an A.I. startup, “elovee”, she influences product strategy through thoughtful and rigorous data analysis.

Date

Feb 24 2021
Expired!

Time

All Day
Category
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