New Book: “No Code Data Science” with Orange and JASP

We are happy to call attention to the book “No Code Data Science: Mastering Advanced Analytics, Machine Learning, and Artificial Intelligence” by David Patrishkoff and Robert E. Hoyt. 

The preface sketches the authors’ goal :

In this age marked by an onslaught of dirty, missing, confusing, collinear, irrelevant, and misleading data, the power of data science lies not only in the hands of coders, but also in the hands of the curious, the innovative, and other analytically skilled individuals who are not coders. “No-Code Data Science” is more than a book; it is a movement, a call to action, and a statement that any inquisitive mind can engage with to extract significant insights from data without being mired in programming language syntaxes.
(…) Here’s to a new dawn of democratized data science.

In exactly 800 pages, the authors enthusiastically use both JASP and Orange to clarify key concepts in data analysis. Throughout the book, they use concrete examples and countless figures. I suspect that from an educational perspective, such an emphasis on application might be what most captures students’ attention. Interested readers should check out the authors’ website, https://www.nocodedatascience.net/, which contains a sample chapter as well as the table of contents.

My own experience generally resonates with that of the authors; whenever I teach a workshop on machine learning (usually with Koen Derks and Don van den Bergh) or on Bayesian inference, it is abundently clear that programs such as JASP allow a highly efficient transition to the key questions that are especially important for beginners: what is the rationale of the methodology? How should the results be interpreted? What factors determine the choice of analysis settings? If you have to spend the first 3 hours explaining the basics of Python or R, this loses time and shifts attention to the very different question “how should I get the software to conduct the intended analysis?” This question will become more relevant as learners progress to higher levels of expertise, but not having to deal with coding from the very beginning is a relief for both students and teachers. Programs such as JASP and Orange make advanced tools available and interesting to a much broader and more diverse audience — as “No Code Data Science” aptly demonstrates.

About the author

Eric-Jan Wagenmakers

Eric-Jan (EJ) Wagenmakers is professor at the Psychological Methods Group at the University of Amsterdam. EJ guides the development of JASP.