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Data Science

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  1. Coffee Break NumPy
    Coffee Break NumPy
    A Simple Road to Data Science Mastery That Fits Into Your Busy Life
    Finxter, Lukas Rieger, and Zohaib Riaz

    Fear of missing out on data science and machine learning?This ​eBook ​gives you a fun way to start learning data science with Python. ​It gives you a thorough introduction Python's most important library for data science: NumPy. 100% Based on puzzle-based learning - scientifically proven to generate ​44% better learning retention and ​efficiency.​

  2. Conversations On Data Science
    Conversations On Data Science
    Roger D. Peng and Hilary Parker

    Roger Peng and Hilary Parker started the Not So Standard Deviations podcast in 2015, a podcast dedicated to discussing the backstory and day to day life of data scientists in academia and industry. This book collects many of their conversations about data science and how it works (and sometimes doesn't work) in the real world.

  3. Risk Analysis in the Earth Sciences
    Risk Analysis in the Earth Sciences
    A Lab Manual with Exercises in R
    Patrick Applegate and Klaus Keller

    Greenhouse gas emissions have caused considerable changes in climate, including increased surface air temperatures and rising sea levels. This e-textbook presents a series of laboratory exercises in R that teach the Earth science and statistical concepts needed for assessing climate-related risks. These exercises are intended for upper-level undergraduates, beginning graduate students, and professionals in other areas who wish to gain insight into academic climate risk analysis.

  4. Patterns We Don't See
    Patterns We Don't See
    Mathematics in Daily Life
    Maksim Balanel

    What if mathematics has been hiding in plain sight all along?A snowflake, a flower, a melody, a crowded street, a city map, a social network, or even a recommendation on your phone — they may seem completely unrelated. But underneath them are patterns, structures, probabilities, and mathematical ideas that quietly shape the world around us.Patterns We Don’t See is an accessible journey into the mathematics of everyday life. You won’t find pages of complicated formulas or a traditional textbook approach. Instead, you’ll discover why certain shapes appear in nature, how music is connected to mathematics, why coincidences feel so surprising, how cities and social networks can be understood as mathematical systems, and how algorithms and artificial intelligence learn to recognize patterns.Written from the perspective of a young engineering student, this book grew from a simple habit: looking at ordinary things and asking, “Where is the mathematics here?”The answer turns out to be: almost everywhere.If you have ever thought that mathematics was only about equations, Patterns We Don’t See invites you to look again.The world hasn’t changed. Only the way we look at it has.

  5. Intuitive Statistics
    Intuitive Statistics
    Mastering basics, Bayes, and AI
    William D. Pearse

    The hardest part of stats is understanding how it all fits together. If you want a book that takes you from the very basics all the way through to the most advanced concepts, this is for you!

  6. The Data Mind
    The Data Mind
    How Thinking Like an Analyst Changes Everyday Decisions
    Soroush Saki

    We all use data every day, often without realizing it. The Data Mind reveals how paying attention to patterns, asking better questions, and thinking more consciously can change the way we make decisions, understand ourselves, and see the world around us.

  7. Longitudinal Data Analysis Using R

    Longitudinal Data Analysis Using R is a practical, end-to-end guide to longitudinal data analysis that helps you move from raw data to credible substantive conclusions. It tackles the real pain points researchers face in longitudinal analysis, such as data preparation, exploring change over time, model choice, missing data, and interpretation, using clear explanations, real-world data, and fully reproducible R code.

  8. Biological Data Science with R

    Biological Data Science with R covers data manipulation with dplyr, visualization with ggplot2, essential statistics, survival analysis, RNA-seq analysis, phylogenetic trees, predictive modeling and infectious disease forecasting, text mining and natural language processing, and more.

  9. Leaving the Rat Race with Python
    Leaving the Rat Race with Python
    An Insider's Guide to Freelance Developing
    Finxter and Lukas Rieger

    Is There a Six-Figure Freelance Developer in You?Leaving the Rat Race with Python shows you how to nurture, grow, and harness your work-from-home coding business online --- and live the good life!It's an insider's guide to freelance developing. Start your new thriving coding business now!

  10. Coffee Break Python - Mastery Workout
    Coffee Break Python - Mastery Workout
    99 Tricky Python Puzzles to Push You to Programming Mastery
    Finxter, Lukas Rieger, and Adrian Chan

    Are you an above-average Python coder? Prove it! Coffee Break Python - Mastery Workout helps you boost your Python skills and reach mastery level. The approach is simple: you solve 99 really hard Python puzzles that get harder as you progress with the book. A clear path to Python mastery!

  11. Discrete Mathematical Algorithm, and Data Structure
    Discrete Mathematical Algorithm, and Data Structure
    Major Components of Mathematics, and Computer Science Explained with the help of C, C++, PHP, Java, C#, Python, and Dart
    Sanjib Sinha

    Readers will learn discrete mathematical abstracts as well as its implementation in algorithm and data structures shown in various programming languages, such as C, C++, PHP, Java, C#, Python and Dart. This book combines two major components of Mathematics and Computer Science under one roof.

  12. Effective Pandas
    Effective Pandas
    Tom Augspurger

    A series on writing effective, idiomatic pandas.

  13. Advanced Statistical Computing

    This book describes the algorithms and procedures used to fit statistical models to data. The material covered is taught in the Advanced Statistical Computing course in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.

  14. Developing Data Products in R
    Developing Data Products in R
    Brian Caffo and Sean Kross

    This book introduces the topic of Developing Data Products in R. A data product is the ideal output of a Data Science experiment. This book is based on the Coursera Class "Developing Data Products" as part of the Data Science Specialization. Particular emphasis is paid to developing Shiny apps and interactive graphics.

  15. Ακαδημαϊκές κατατάξεις στην ελληνική ανώτατη εκπαίδευση, Έκδοση 2026
    Ακαδημαϊκές κατατάξεις στην ελληνική ανώτατη εκπαίδευση, Έκδοση 2026
    Πλήρης βιβλιομετρική αποτίμηση των ελληνικών πανεπιστημιακών Τμημάτων και των μελών ΔΕΠ
    Stelios Bekiros

    Η πρώτη πλήρης βιβλιομετρική αποτίμηση κάθε ελληνικού πανεπιστημιακού Τμήματος και των μόνιμων μελών ΔΕΠ: 23 πανεπιστήμια, 339 Τμήματα και 8.809 μέλη, σε τρεις βιβλιομετρικές πηγές.