Chief Data Scientist at Reorg, a global provider of credit intelligence, data and analytics, and Adjunct at UVA’s School of Data Science. Finance is an evergreen field with an abundance of data. There ...

“The data science master’s program at UB has helped me to bridge the technical gaps between my undergraduate mathematics background and the skills required to start out in the data science industry.

To apply for the Computational and Data-Enabled Sciences PhD program, students should hold a master's degree in a related field, including but not limited to engineering, computer science, mathematics ...

Develop interdisciplinary skills in data science and gain knowledge of statistical analysis, data mining, and machine learning from one of the nation’s top-ranked Tier 1 research institutions. Earn ...

Within this page, you can find information about how to apply for the Master of Science in Data Science (MSDS) or Foundations of Data Science Graduate Certificate. Review program requirements, as well ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

In an era when data-driven decisions and systems influence every sector of business and society, talented professionals who bring an ethical framework to data science are more in demand than ever. The ...

The Michigan Tech Data Science MS provides a broad-based education in data mining, predictive analytics, cloud computing, data-science fundamentals, communication, and business acumen. You'll gain a ...

Business investment in data science is one of the most important advances of the past decade. While some may argue data science has already worked its way into every industry, there are still areas ...

NIC invites applications for Scientist B posts across computer science, electronics, and data science disciplines until April ...

For people working across the philanthropic sector, data science can feel like an unwieldy topic. Where do you start? What data is important? How does it fit into your community work? Before you get ...