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, ...

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 ...

In an effort to remain competitive in today’s increasingly challenging economic times, companies are moving forward with digital transformations — powered by data science and machine learning — at an ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

Capstone projects are academic semester-long experiences for students nearing graduation. Student teams complete a substantial data science project that solidifies knowledge gained in the classroom ...

“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Ellen Houston, managing director of ...

Data science startup RapidCanvas Inc. today announced that it closed a $16 million funding round led by Peak XV,. Titanium Ventures, Accel and Valley Capital Partners also contributed to the ...