As I frequently travel in data science circles, I’m hearing more and more about a new kind of tech war: Python vs. R. I’ve lived through many tech wars in the past, e.g. Windows vs. Linux, iPhone vs.

R vs Python: What are the main differences? Your email has been sent More people will find their way to Python for data science workloads, but there’s a case to for making R and Python complementary, ...

Java can handle large workloads, and even if it hits limitations, peripheral JVM languages such as Scala and Kotlin can pick up the slack. But in the world of data science, Java isn't always the go-to ...

When it comes to choosing a programming language, there really are only two choices if you’re working with data. For data science, machine learning, statistics, IoT technology and even automation, the ...

Advanced statistical modelling, hypothesis testing, and academic workflows make R preferred for data-heavy research and reproducible ...

Reticulate is a handy way to combine Python and R code. From the reticulate help page suggests that reticulate allows for: "Calling Python from R in a variety of ways including R Markdown, sourcing ...

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 ...

Eastern University’s Certificate in Data Science is a 100% online, self-paced program designed for post-baccalaureate ...