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 ...

Learn how to use Google Colab for coding, data science, and AI projects with this beginner-friendly guide. Free GPU access ...

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 ...

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 ...

When working on a data-driven project, finding reliable and high-quality data sets is essential. Fortunately, there are several free sources available that provide access to a wide range of data sets ...

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, ...

Most go off course. To make sure yours succeed, consider these five steps. by Iavor Bojinov When I worked as a data scientist at LinkedIn in 2018 and 2019, AI was of interest only to a small team of ...

Johns Hopkins University presented revised plans for its new?Data Science and Artificial Intelligence?(DSAI) facility to Baltimore's Urban Planning Architecture Advisory Panel (UDAAP) on Thursday, ...

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 ...