PSG IM Professors author book on Data Science

Two Associate Professors at PSG Institute of Management (PSG IM) Dr.Uma Maheswari and Dr.Sujatha have authored the book ‘Introduction to Data Science -Practical Approach with R and Python’. It was published by Wiley India as a part of Wiley Emerging Technology Series and got released on Monday at the college premises.

Karti Purushothaman, Partner, McKinsey & Co, Jayanth Bagare, Chief Architect, SAP Engineering Academy launched the book in the presence of Dr.T.J.Vijaya, Director (i/c) PSG IM.

It is a 584-pages book that can cater to the growing needs of the industry and academia. The book deals with concepts of Data Science through open source programming languages ‘R’ and ‘Python’. It presents coding in a highly simplified manner enhanced by visual aids of the output and introduces concepts in a simple language with practical application based on real-world scenario. The book also includes case-studies, practice datasets, mini projects and internet exercises.

Both professors serve as adjunct faculty of University of Toledo. Dr. B. Uma Maheswari belongs to the Decision Sciences stream at PSG IM. An academician with around two decades of experience, she specializes in the field of strategic management, business analytics, design thinking, and entrepreneurship.

Dr.Sujatha has been teaching at PSG IM since 2000. She has more than two decades of wide-ranging experience in teaching, research, and consulting at PSG Institute of Management. Her research interests include analytics, optimization of supply chain networks, and lean management.

Who can get benefited from this book?

This book serves as a practical guide for Science/Engineering/Management students – both at the undergraduate and postgraduate level interested in Data Science domain.

The purpose of the book would be to serve as a practical guide for science/engineering/management students interested in the data science domain. It offers a mix of insights and golden rules which would be needed in analyzing the data.

It is suitable for courses on data science, data analytics, business intelligence, data mining, business analytics, and machine learning. The book will also be useful for special electives requiring higher learning as it concentrates on current topics such as Artificial Neural Networks and Artificial Intelligence.