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mariadas s data science foundations navigating digital insight 2025

Type:: E-books
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Uploaded On:: April 30, 2025, 8:20 a.m.
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Textbook in PDF format While Data Science is powering most modern organisations its technical intricacies often remain confined to a select few. This book is for those starting to work within this field to give them the foundations on which to build their confidence and understanding. Allowing them to contribute to projects through making decisions and acting on them. Written in an accessible manner, Data Science Foundations provides explanations of complex concepts and methods in layman’s terms supported by examples. It also includes a holistic view of Data Science covering the technical, ethical and delivery challenges illustrated by case studies. Aligned with industry-recognised qualifications, this is the definitive guide for aspiring data scientists, providing a solid foundation in data analysis techniques. Data science involves applying the right tools and techniques to analyse data and build models. The tools you choose will depend on your team’s expertise and the complexity of the project. Popular tools • Excel: Spreadsheet software that is versatile and accessible, a great starting point. • Python or R: For data analysis, machine learning and visualisation. • SQL: For querying databases. • Tableau or Power BI: For creating dashboards and visualisations. • Cloud platforms: AWS, Google Cloud or Azure for handling large-scale projects. "A brilliant guide to Data Science. Covers the full lifecycle with clarity and practical insight – perfect for newcomers but a fantastic reference for all." - Chris Weston, Technology Consultant, NashTech "Data Science Foundations is the perfect beginner’s guide, offering a clear, engaging overview of key concepts with real-world examples. A must-read companion for anyone eager to dive into Data Science." - Jake Wilson PhD, Data Scientist, GHGSat Inc. "A fantastic introduction to Data Science, covering problem definition, statistics, model selection, communication and visualisation. Clear and concise, it’s an excellent starting point for anyone new to the field!" - Richard Fritz-Hewer, Data Scientist, CMC Partnership Preface INTRODUCTION STAKEHOLDERS PROJECT DELIVERY ETHICS AND LAWFULNESS DISCOVERY SOURCING PREPARATION BASIC CONCEPTS MODEL SELECTION ... MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE CASE STUDIES CONCLUSION

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Mariadas S. Data Science Foundations. Navigating digital insight 2025.pdf 14.9 MB

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mariadas s data science foundations navigating digital insight 2025

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