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.

Humans produce more than 2.5 million terabytes of data every day. From social media use to scientific studies to financial transactions, every action that is digitally recorded is a piece of data that ...

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 ...

Design thinking is critical for developing data-driven business tools that surpass end-user expectations. Here's how to apply the five stages of design thinking in your data science projects. What is ...

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 ...

The Johns Hopkins Data Science and AI Institute announces the launch of the Demonstration Projects funding program, aimed at accelerating the development and deployment of data science (DS) and ...

These days, most people are aware of both the buzz and consternation that has accompanied any discussion of artificial intelligence (AI) within recent months. Like any technology, AI has a learning ...

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 ...

Both fields are in high demand, pay well, and lead to exciting, future-proof careers. If you're deciding between becoming a data scientist or an AI engineer, the choice often comes down to what ...

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 ...