Overview:  Python and Jupyter offer a simple, powerful setup for beginner-friendly data science learning. Real-world datasets ...

While you can do some good data analysis with a spreadsheet like Excel, if you want to take your calculations to the next level, you might try Python in a Jupyter notebook instead. Here are some ...

Data scientists are explorers. They use Jupyter Notebooks, one of the most popular environments for data science analysis, to begin work toward creative solutions to big problems. But once those ...

These days, the industry would have you believe that data and analytics is all being done in the service of AI. And, given that, there's a lot of orientation toward data scientists' seemingly favorite ...

Big data refers to datasets that are too large, complex, or fast-changing to be handled by traditional data processing tools. It is characterized by the four V's: Big data analytics plays a crucial ...

A computer code co-developed by a scientist from Lawrence Berkeley National Laboratory (Berkeley Lab) and embraced by the global science community over two decades has been hailed by Nature Magazine ...

In this RCE Podcast, Brock Palen and Jeff Squyres discuss Project Jupyter with Dr. Brian Granger from Cal Poly State University. Jupyter exists to develop open-source software, open-standards, and ...

Interactive Python modes are an easy way to learn new libraries. Scripting languages are easy to learn on their own because ...

They cover key skills such as Python, SQL, statistics, machine learning, deep learning, data engineering, MLOps and ...

At some point, we all need to show our work. Most programming work is shared either as raw source code or as a compiled executable. The source code provides complete information, but in a way that’s ...