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.

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 ...

Nino Letteriello is a data and project management leader, DAMA Award winner, WEF author, UN advisor, MIT lecturer & FIT Group co-founder. A significant percentage of data science projects continue to ...

Moving data science into production has quite a few similarities to deploying an application. But there are key differences you shouldn’t overlook. Agile programming is the most-used methodology that ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your toolkit. Python’s rich ecosystem of data science tools is a big draw for ...

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 last decade has seen an explosion of data generation from individuals, businesses and institutions worldwide. As these organizations increasingly rely on data-driven decision-making, the demand ...

Purdue University’s online Master’s in Data Science will mold the next generation of data science experts and data engineers to help meet unprecedented industry demand for skilled employees. The ...