The Decision Makers Handbook to Data Science – Stylianos Kampakis
“Great read and excellent real-life examples of the need, usefulness and applications of data science in day-to-day business decision making.” – SF82
Data science is about using data
to do useful stuff.
Short and to the point. That’s exactly what data science is all about. The methods we use are important, of course, but the essence of this discipline is that it allows us to take data and transform it so we can use it to do useful things.
Have you ever felt confused by terms such as ‘data science’ and ‘big data’? What is really the difference between AI and machine learning? How can you hire a good data scientist and how do you build a data-driven organisation? Have you ever thought you’d like to use data-science, but you don’t know where to start?
The Decision Maker’s Handbook to Data Science was written specifically for you. It covers all the topics that a non-technical decision maker needs to know in order to use data science within an organisation.
Driven by the author’s 10+ years of experience, the book’s aim is to demystify the jargon and offer answers to all the most common problems and questions that decision makers face when dealing with data. Topics include:
1) Explaining data science. Demystifying the differences between AI, machine learning and statistics.
2) Data management best practices.
3) How to think like a data scientist, without being one.
4) How to hire and manage data scientists.
5) How to setup the right culture in an organisation, in order to make it data-centric.
6) Case studies and examples based on real scenarios.
Data science, machine learning and artificial intelligence are amongst the main drivers of the technological revolution we are experiencing. If you are planning to collect and use data within your company, then the Decision Maker’s Handbook to Data Science will help you avoid the most common mistakes and pitfalls, and make the most out of your data.
“Avoids technical details and focuses instead on the concepts and applications of data science in business. Recommended to anyone without a technical background.” – Vassilis
“Given all the hype around data science Dr. Kampakis unpacks the term and related fields with helpful clarity and insight. Very useful for business decision makers that understand the inescapable impact the field has on their success, yet may currently feel a little lost.” – Mira M Wilfert
About the Author
Dr. Stylianos (Stelios) Kampakis is a data scientist who lives and works in London, UK. He holds a PhD in Computer Science from University College London, as well as an MSc in Informatics from the University of Edinburgh. He holds degrees in Statistics, Cognitive Psychology, Economics and Intelligent Systems. Stylianos is a member of the Royal Statistical Society and an honorary research fellow in the UCL Centre for Blockchain Technologies. He has many years of academic and industrial experience in all fields of data science: statistical modelling, machine learning, classic AI, optimisation and many more.
Stylianos’ academic experience ranges across various domains. He is one of the foremost experts in the area of sports analytics, having done his PhD in the use of machine learning for predicting football injuries. He has also done work in the area of neural networks, computational neuroscience and cognitive science. Currently, he is doing research in blockchain and more specifically in the area of tokenomics, where he studies topics such as the best mechanisms for handling volatility in token economies and evaluating Initial Coin Offerings (ICOs).
Some of the many companies Stylianos has consulted for have gone on to raise millions in funding.
Stylianos is also very active in the area of data science education. He is the founder of The Tesseract Academy, a company whose mission is to help decision makers understand deep technical topics such as machine learning and blockchain. He is also teaching Social Media Analytics and Quantitative Methods & Statistics with R in the Cyprus International Institute of Management.
He frequently expresses his views about technology and other matters at his personal webpage, The Data Scientist
“This book really helped me understand how data science can be applied in my field, and how many of the problems I face in my work can be solved through machine learning. Excellent job explaining terms with simple, “lay” language and illustrations.” – Panos V