Data Science Foundations And Hands On Experience
DOWNLOAD
Download Data Science Foundations And Hands On Experience PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Science Foundations And Hands On Experience book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Data Science Foundations And Hands On Experience
DOWNLOAD
Author : Fatwa Ramdani
language : en
Publisher: Springer Nature
Release Date : 2025-06-18
Data Science Foundations And Hands On Experience written by Fatwa Ramdani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-18 with Computers categories.
This book will take readers from foundational concepts to practical applications, enabling them to transform raw data into meaningful insights. It covers key skills such as data collection, cleaning, organization, exploration, analysis, and impactful presentation—core competencies for navigating today’s data-rich landscape. Each chapter is designed to build both theoretical understanding and hands-on expertise. The book’s unique dual-approach structure introduces foundational data science concepts, followed by exercises in RStudio using real-world datasets from social fields. This blend of theory and practice ensures readers grasp the ‘how’ and the ‘why’ behind data-driven research, making it ideal for students, researchers, and professionals seeking to enhance their analytical capabilities. Spatial data analysis stands out as one of the most unique in this book because it focuses on spatial data, a topic rarely covered in data science references. While there are many resources on data science, few explore the unique aspects of spatial data. Nowadays, most data includes location information, which can greatly enhance data science and decision-making. The final chapter will discuss critical topics in data ethics and reproducibility, encouraging readers to think responsibly about data use. By the end, readers will gain not only technical skills but also ethical awareness, empowering them to conduct rigorous, reliable, and socially conscious research. No prior experience with data science is required—just an eagerness to explore the power of data in understanding and shaping society. This textbook is suitable for adoption in both undergraduate and graduate classes. The book will help students build a solid theoretical foundation in data science while gaining hands-on experience with RStudio.
A Hands On Introduction To Data Science
DOWNLOAD
Author : Chirag Shah
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-02
A Hands On Introduction To Data Science written by Chirag Shah and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Business & Economics categories.
An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.
Data Science Foundation Fundamentals
DOWNLOAD
Author : Mr. Ramkumar A
language : en
Publisher: Xoffencerpublication
Release Date : 2023-08-21
Data Science Foundation Fundamentals written by Mr. Ramkumar A and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-21 with Computers categories.
The academic field of computer science did not develop as a separate subject of study until the 1960s after it had been in existence since the 1950s. The mathematical theory that underpinned the fields of computer programming, compilers, and operating systems was one of the primary focuses of this class. Other important topics were the various programming languages and operating systems. Context-free languages, finite automata, regular expressions, and computability were a few of the topics that were discussed in theoretical computer science lectures. The area of study known as algorithmic analysis became an essential component of theory in the 1970s, after having been mostly overlooked for the majority of its existence up to that point in time. The purpose of this initiative was to investigate and identify practical applications for computer technology. At the time, a significant change is taking place, and a greater amount of attention is being paid to the vast number of different applications that may be utilized. This shift is the cumulative effect of several separate variables coming together at the same time. The convergence of computing and communication technology has been a major motivator, and as a result, this change may be primarily attributed to that convergence. Our current knowledge of data and the most effective approach to work with it in the modern world has to be revised in light of recent advancements in the capability to monitor, collect, and store data in a variety of fields, including the natural sciences, business, and other fields. This is necessary because of the recent breakthroughs in these capabilities. This is as a result of recent advancements that have been made in these capacities. The widespread adoption of the internet and other forms of social networking as indispensable components of people's lives brings with it a variety of opportunities for theoretical development as well as difficulties in actual use. Traditional subfields of computer science continue to hold a significant amount of weight in the field as a whole; however, researchers of the future will focus more on how to use computers to comprehend and extract usable information from massive amounts of data arising from applications rather than how to make computers useful for solving particular problems in a well-defined manner. This shift in emphasis is due to the fact that researchers of 1 | P a ge the future will be more concerned with how to use computers to comprehend and extract usable information from massive amounts of data arising from applications. This shift in emphasis is because researchers of the future will be more concerned with how to use the information they find. As a result of this, we felt it necessary to compile this book, which discusses a theory that would, according to our projections, play an important role within the next 40 years. We think that having a grasp of this issue will provide students with an advantage in the next 40 years, in the same way that having an understanding of automata theory, algorithms, and other topics of a similar sort provided students an advantage in the 40 years prior to this one, and in the 40 years after this one. A movement toward placing a larger emphasis on probabilities, statistical approaches, and numerical processes is one of the most significant shifts that has taken place as a result of the developments that have taken place. Early drafts of the book have been assigned reading at a broad variety of academic levels, ranging all the way from the undergraduate level to the graduate level. The information that is expected to have been learned before for a class that is taken at the undergraduate level may be found in the appendix. As a result of this, the appendix will provide you with some activities to do as a component of your project.
Introduction To Data Science
DOWNLOAD
Author : Laura Igual
language : en
Publisher: Springer
Release Date : 2017-02-22
Introduction To Data Science written by Laura Igual and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-22 with Computers categories.
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
Data Science Foundations Tools And Techniques
DOWNLOAD
Author : Michael Freeman
language : en
Publisher: Addison-Wesley Professional
Release Date : 2018-11-16
Data Science Foundations Tools And Techniques written by Michael Freeman and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-16 with Application software categories.
The Foundational Hands-On Skills You Need to Dive into Data Science "Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills." -From the foreword by Jared Lander, series editor Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience. Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you've uncovered. Step by step, you'll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales. Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything's focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to Install your complete data science environment, including R and RStudio Manage projects efficiently, from version tracking to documentation Host, manage, and collaborate on data science projects with GitHub Master R language fundamentals: syntax, programming concepts, and data structures Load, format, explore, and restructure data for successful analysis Interact with databases and web APIs Master key principles for visualizing data accurately and intuitively Produce engaging, interactive visualizations with ggplot and other R packages Transform analyses into sharable documents and sites with R Markdown Create interactive web data science applications with Shiny Collaborate smoothly as part of a data science team Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Data Science Thinking
DOWNLOAD
Author : Longbing Cao
language : en
Publisher: Springer
Release Date : 2018-08-17
Data Science Thinking written by Longbing Cao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-17 with Computers categories.
This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.
Foundations Of Data Science
DOWNLOAD
Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23
Foundations Of Data Science written by Avrim Blum and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.
Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.
Data Science For Undergraduates
DOWNLOAD
Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2018-10-11
Data Science For Undergraduates written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-11 with Education categories.
Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.
Strategic Guidance For The National Science Foundation S Support Of The Atmospheric Sciences
DOWNLOAD
Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2007-07-01
Strategic Guidance For The National Science Foundation S Support Of The Atmospheric Sciences written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-01 with Science categories.
The National Science Foundation's Division of Atmospheric Sciences (ATM) supports research to develop new understanding of Earth's atmosphere and how the Sun impacts it. Strategic Guidance for the National Science Foundation's Support of the Atmospheric Sciences provides guidance to ATM on its strategy for achieving its goals in the atmospheric sciences, including cutting-edge research, education and workforce development, service to society, computational and observational objectives, and data management. The report reviews how the atmospheric sciences have evolved over the past several decades and analyzes the strengths and limitations of the various modes of support employed by ATM. It concludes that ATM is operating in an environment that is ever more cross-disciplinary, interagency, and international, making a more strategic approach necessary to manage activities in a way that actively engages the atmospheric sciences community. At the same time, ATM should preserve opportunities for basic research, especially projects that are high risk, potentially transformative, or unlikely to be supported by other government agencies. Finally, ATM needs to be more proactive in attracting highly talented students to the atmospheric sciences as an investment in the ability to make future breakthroughs.
Annual Report For Fiscal Year
DOWNLOAD
Author : National Science Foundation (U.S.)
language : en
Publisher:
Release Date : 1981
Annual Report For Fiscal Year written by National Science Foundation (U.S.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Research categories.