Data science refers to an interdisciplinary field that involves a series of methods, processes, and systems, with the aim of extracting knowledge from data. There are many learning-related processes involved, and great amounts of potential rich data are generated in educational institutions continuously. The application of data science is of great interest for stakeholders such as students, instructors, and institutions, because the extracted knowledge from educational data would be useful to deal with educational problems such as student performance, high churning rates in educational institutions, learning delays, and more.
This major reference work presents the data science journey from theory and concepts, methods, techniques, tools, and recent trends in data science technologies. It highlights the comparison among the existing techniques of various problems in data analytics, visualization, and other related fields. Covering topics such as educational data science, predictive analytics, and applied mathematics, this book is an excellent resource for academicians, IT and medical professionals, researchers, and stakeholders currently working in the field.