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Data Science For Public Policy


Data Science For Public Policy
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Data Science For Public Policy


Data Science For Public Policy
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Author : Jeffrey C. Chen
language : en
Publisher: Springer Nature
Release Date : 2021-09-01

Data Science For Public Policy written by Jeffrey C. Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-01 with Mathematics categories.


This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst’s time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.



Science For Public Policy


Science For Public Policy
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Author : H. Brooks
language : en
Publisher: Elsevier
Release Date : 2013-10-22

Science For Public Policy written by H. Brooks and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-22 with Political Science categories.


Since World War II, national and international policy makers have been confronted by a growing number of complex problems the resolution of which hangs, to a significant degree, on scientific knowledge or technical insights. This puts a premium on the quality and clarity of scientific/technical advice they receive. From their vantage points as scientists, policy makers or science advisors from both East and West, the authors of this book examine the issues involved in science for public policy and explore ways to improve the quality and timeliness of the scientific advice available to decision makers. Environmental problems provide much of the focus for the analysis.



Envisioning The Data Science Discipline


Envisioning The Data Science Discipline
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2018-03-05

Envisioning The Data Science Discipline 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 2018-03-05 with Education categories.


The need to manage, analyze, and extract knowledge from data is pervasive across industry, government, and academia. Scientists, engineers, and executives routinely encounter enormous volumes of data, and new techniques and tools are emerging to create knowledge out of these data, some of them capable of working with real-time streams of data. The nation's ability to make use of these data depends on the availability of an educated workforce with necessary expertise. With these new capabilities have come novel ethical challenges regarding the effectiveness and appropriateness of broad applications of data analyses. The field of data science has emerged to address the proliferation of data and the need to manage and understand it. Data science is a hybrid of multiple disciplines and skill sets, draws on diverse fields (including computer science, statistics, and mathematics), encompasses topics in ethics and privacy, and depends on specifics of the domains to which it is applied. Fueled by the explosion of data, jobs that involve data science have proliferated and an array of data science programs at the undergraduate and graduate levels have been established. Nevertheless, data science is still in its infancy, which suggests the importance of envisioning what the field might look like in the future and what key steps can be taken now to move data science education in that direction. This study will set forth a vision for the emerging discipline of data science at the undergraduate level. This interim report lays out some of the information and comments that the committee has gathered and heard during the first half of its study, offers perspectives on the current state of data science education, and poses some questions that may shape the way data science education evolves in the future. The study will conclude in early 2018 with a final report that lays out a vision for future data science education.



Data Science Careers Training And Hiring


Data Science Careers Training And Hiring
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Author : Renata Rawlings-Goss
language : en
Publisher: Springer
Release Date : 2019-08-02

Data Science Careers Training And Hiring written by Renata Rawlings-Goss and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-02 with Education categories.


This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build.



Data Science For Undergraduates


Data Science For Undergraduates
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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.



Data Analytics For The Social Sciences


Data Analytics For The Social Sciences
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Author : G. David Garson
language : en
Publisher: Routledge
Release Date : 2021-11-29

Data Analytics For The Social Sciences written by G. David Garson and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Psychology categories.


Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.



The Science Of Public Policy Evolution Of Policy Sciences Pt 2


The Science Of Public Policy Evolution Of Policy Sciences Pt 2
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Author : Tadao Miyakawa
language : en
Publisher: Taylor & Francis
Release Date : 1999

The Science Of Public Policy Evolution Of Policy Sciences Pt 2 written by Tadao Miyakawa and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Political Science categories.




A Hands On Introduction To Data Science


A Hands On Introduction To Data Science
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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.



Artificial Intelligence In Government


Artificial Intelligence In Government
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Author : Rodrigo Sandoval-Almazán
language : en
Publisher: Springer Nature
Release Date : 2025-06-18

Artificial Intelligence In Government written by Rodrigo Sandoval-Almazán 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 Political Science categories.


​ This edited volume discusses the challenges of digital transformation in Latin America, specifically regarding the use of AI for government management in the public sector. This book brings together leading scholars and practitioners from the region to address the legal and regulatory frameworks needed to introduce AI into government processes, as well as the infrastructure requirements for successful implementation. It explores potential resistance from public officials towards technology adoption and ways to overcome it. Moreover, the book considers the digital divide that exists within Latin American societies, which may hinder access to AI tools for some citizens. It also discusses ethical considerations related to AI use in government processes, such as privacy concerns and algorithmic bias. Providing a comprehensive understanding of the challenges and opportunities that AI presents for Latin American governments, this volume will be of use to students and scholars interested in governance, public management, AI, and Latin American studies.



Data Science Exam Preparation


Data Science Exam Preparation
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Author : cybellim
language : en
Publisher: Cybellium Ltd
Release Date : 2024-10-26

Data Science Exam Preparation written by cybellim and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with Study Aids categories.


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