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The Decision Maker's Handbook to Data Science: AI and Data Science for Non-Technical Executives, Managers, and Founders

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Book Details
Language
English
Publishers
Apress; Third edition (2 July 2024)
Weight
0.29 KG
Publication Date
15/07/2024
Pages
197 pages
ISBN-13
9798868802782
Dimensions
15.5 x 1.17 x 23.5 cm
SKU
9798868802782
Author Name
Stylianos Kampakis (Author)
Dr Stylianos (Stelios) Kampakis is a data science veteran and tokenomics expert. He has worked with decision makers from companies of all sizes: from startups to organisations like the US Navy, Vodafone and British Land. His work expands multiple sectors including fintech, sports analytics, health-tech, general AI, medical statistics, predictive maintenance and others. He has 2 patents pending to his name.He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School and CEO of The Tesseract Academy http://tesseract.academy.He was also one of the first researchers in the area of blockchain to study tokenomics. His seminal work in token economics has led to many successful token economic designs using tools such as agent based modelling and game theory.He blogs regularly at The Data Scientist http://thedatascientist.comRead more about this authorRead less about this author
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Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization.

This third edition delves into the latest advancements in AI, particularly focusing on large language models (LLMs), with clear distinctions made between AI and traditional data science, including AI's ability to emulate human decision-making. Author Stylianos Kampakis introduces you to the critical aspect of ethics in AI, an area of growing importance and scrutiny.

The narrative examines the ethical considerations intrinsic to the development and deployment of AI technologies, including bias, fairness, transparency, and accountability. You’ll be provided with the expertise and tools required to develop a solid data strategy that is continuously effective.

Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated edition also includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists.

Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization.

The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will LearnIntegrate AI with other innovative technologies Explore anticipated ethical, regulatory, and technical landscapes that will shape the future of AI and data scienceDiscover how to hire and manage data scientistsBuild the right environment in order to make your organization data-drivenWho This Book Is ForStartup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists.

A secondary audience includes people looking for a soft introduction into the subject of data science. .

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