Beginners should undertake data science projects as they provide practical experience and help in the application of theoretical concepts learned in courses, building a portfolio and enhancing skills.

“If your competitors are applying AI, and they’re finding insight that allow them to accelerate, they’re going to peel away really, really quickly,” Deborah Leff, CTO for data science and AI at IBM, ...

Nine data-driven research projects have won funding from Princeton University’s Schmidt DataX Fund, which aims to spread and deepen the use of artificial intelligence and machine learning across ...

Responding to an impending hazard means that time is limited, so analysis and decision-making must proceed on an accelerated timetable. Modeling, numerical simulation, leading to predictive capacity, ...

Did you know that over 80% of AI projects fail? That's twice the failure rate of regular IT projects. A Gartner survey found that only 48% of AI projects make it to production, and it typically takes ...

Shivanku Misra is an AI expert, currently serving as Vice President overseeing enterprise advanced analytics and AI initiatives at McKesson. In the rapidly evolving field of data science, the success ...