How to Think About Data Science

This book is a timely and critical introduction for people who are interested in what data science is (and isn't), and how it should be applied. The language is conversational and the content is accessible for readers without a quantitative or computational background.

About the author

Diego Miranda Saavedra is a data scientist and a financial investor with a technical management and business background. His formal education includes a PhD (data analysis), an MSc in business analytics, and an MS in software engineering from the University of Oxford.
As part of a research career in data science, Diego has made seminal contributions and worked in renowned research institutes around the world. These include the Wellcome Trust Biocentre (Dundee, UK), the Cambridge Institute for Medical Research (Cambridge, UK) and the WPI Immunology Frontier Research Center (Osaka University, Japan) where he led the bioinformatics and genomics research laboratory. While at the University of Cambridge, Diego was also elected a fellow of Wolfson College.
Diego also loves teaching data science and is currently an adjunct professor at the Faculty of Economics of the University of Groningen and at the Universitat Oberta de Catalunya.

Summary

This book is a timely and critical introduction for people who are interested in what data science is (and isn’t), and how it should be applied. The language is conversational and the content is accessible for readers without a quantitative or computational background.

Product details

• Authors: Diego Miranda-Saavedra
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 23.12.2022
• EAN: 9781032375687
• ISBN: 978-1-0-3237568-7
• No. of pages: 276
• Series: Chapman & Hall/CRC Data Science Series
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Artificial Intelligence, COMPUTERS / Computer Science, COMPUTERS / Programming / Games, Probability & statistics, Mathematical & statistical software, Databases, Probability and statistics, COMPUTERS / Data Science / Machine Learning, COMPUTERS / Data Science / Data Visualization, COMPUTERS / Data Science / Data Analytics, Mathematical and statistical software