| colorado boulder data science: Data Science for Undergraduates National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-11-11 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. |
| colorado boulder data science: Sustainable Statistical and Data Science Methods and Practices O. Olawale Awe, Eric A. Vance, 2024-01-05 This volume gathers papers presented at the LISA 2020 Sustainability Symposium in Kumasi, Ghana, May 2–6, 2022. They focus on sustainable methods and practices of using statistics and data science to address real-world problems. From utilizing social media for statistical collaboration to predicting obesity among rural women, and from analyzing inflation in Nigeria using machine learning to teaching data science in Africa, this book explores the intersection of data, statistics, and sustainability. With practical applications, code snippets, and case studies, this book offers valuable insights for researchers, policymakers, and data enthusiasts alike. The LISA 2020 Global Network aims to enhance statistical and data science capability in developing countries through the creation of a network of collaboration laboratories (also known as “stat labs”). These stat labs are intended to serve as engines for development by training the next generation of collaborative statisticians and data scientists, providing research infrastructure for researchers, data producers, and decision-makers, and enabling evidence-based decision-making that has a positive impact on society. The research conducted at LISA 2020 focuses on practical methods and applications for sustainable growth of statistical capacity in developing nations. |
| colorado boulder data science: The Crystal Ball Instruction Manual, Volume One Stephen Davies, 2020-08-10 A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background. |
| colorado boulder data science: Ambitious Science Teaching Mark Windschitl, Jessica Thompson, Melissa Braaten, 2020-08-05 2018 Outstanding Academic Title, Choice Ambitious Science Teaching outlines a powerful framework for science teaching to ensure that instruction is rigorous and equitable for students from all backgrounds. The practices presented in the book are being used in schools and districts that seek to improve science teaching at scale, and a wide range of science subjects and grade levels are represented. The book is organized around four sets of core teaching practices: planning for engagement with big ideas; eliciting student thinking; supporting changes in students’ thinking; and drawing together evidence-based explanations. Discussion of each practice includes tools and routines that teachers can use to support students’ participation, transcripts of actual student-teacher dialogue and descriptions of teachers’ thinking as it unfolds, and examples of student work. The book also provides explicit guidance for “opportunity to learn” strategies that can help scaffold the participation of diverse students. Since the success of these practices depends so heavily on discourse among students, Ambitious Science Teaching includes chapters on productive classroom talk. Science-specific skills such as modeling and scientific argument are also covered. Drawing on the emerging research on core teaching practices and their extensive work with preservice and in-service teachers, Ambitious Science Teaching presents a coherent and aligned set of resources for educators striving to meet the considerable challenges that have been set for them. |
| colorado boulder data science: Research in Data Science Ellen Gasparovic, Carlotta Domeniconi, 2019-03-25 This edited volume on data science features a variety of research ranging from theoretical to applied and computational topics. Aiming to establish the important connection between mathematics and data science, this book addresses cutting edge problems in predictive modeling, multi-scale representation and feature selection, statistical and topological learning, and related areas. Contributions study topics such as the hubness phenomenon in high-dimensional spaces, the use of a heuristic framework for testing the multi-manifold hypothesis for high-dimensional data, the investigation of interdisciplinary approaches to multi-dimensional obstructive sleep apnea patient data, and the inference of a dyadic measure and its simplicial geometry from binary feature data. Based on the first Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place in 2017 at the Institute for Compuational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, this volume features submissions from several of the working groups as well as contributions from the wider community. The volume is suitable for researchers in data science in industry and academia. |
| colorado boulder data science: A Modern Introduction to Probability and Statistics F.M. Dekking, C. Kraaikamp, H.P. Lopuhaä, L.E. Meester, 2006-03-30 Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books |
| colorado boulder data science: Roundtable on Data Science Postsecondary Education National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Division on Engineering and Physical Sciences, Board on Science Education, Computer Science and Telecommunications Board, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, 2020-10-02 Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting. |
| colorado boulder data science: Recent Advancement in Geoinformatics and Data Science Xiaogang Ma, Matty Mookerjee, Leslie Hsu, Denise Hills, 2023-04-11 |
| colorado boulder data science: DEEP LEARNING FOR DATA MINING: UNSUPERVISED FEATURE LEARNING AND REPRESENTATION Srinivas Babu Ratnam, Jesús A. Coloma, Dr. Herison Surbakti , Haewon Byeon, 2023-07-03 Several empirical research have come to the conclusion that the representation of data plays a vital role in the efficiency with which machine learning algorithms complete their tasks. This indicates that the design of feature extraction, preprocessing, and data transformations requires a disproportionate amount of time and resources when actually executing machine learning algorithms. These steps include preparing the data for analysis, extracting features from the data, and processing the data. This is because each of these components is essential to the algorithm as a whole in order for it to function properly. In spite of the fact that it is of the utmost significance, feature engineering calls for a significant amount of human effort. It also shows a shortcoming of the learning algorithms that are now in use, which is their inability to extract all of the pertinent characteristics from the data that is currently accessible. This is a difficulty with the approaches that are currently utilized in the process of learning. An approach that may be utilized to make up for such a shortfall is called feature engineering, and it involves making use of human intelligence in conjunction with prior information. It would be extremely desired to make learning algorithms less dependent on feature engineering in order to expedite the production of innovative applications and, more crucially, to realize advancements in artificial intelligence (AI). This would be done in order to achieve developments in AI. There are two possible consequences resulting from this. This would make it possible to use machine learning in a larger variety of applications that are simpler to put into action, which would increase the value of machine learning. An artificial intelligence has to have at least a fundamental comprehension of the environment in which humans live, and this may be accomplished if a learner is able to interpret the concealed explanatory factors that are embedded within the visible milieu of low-level sensory input. It is conceivable to combine feature engineering with feature learning in order to obtain state-of-the-art solutions that can be applied to actual circumstances in the real world. |
| colorado boulder data science: Big Data Analytics in Earth, Atmospheric, and Ocean Sciences Thomas Huang, Tiffany C. Vance, Christopher Lynnes, 2022-10-14 Applying tools for data analysis to the rapidly increasing volume of data about the Earth An ever-increasing volume of Earth data is being gathered. These data are “big” not only in size but also in their complexity, different formats, and varied scientific disciplines. As such, big data are disrupting traditional research. New methods and platforms, such as the cloud, are tackling these new challenges. Big Data Analytics in Earth, Atmospheric, and Ocean Sciences explores new tools for the analysis and display of the rapidly increasing volume of data about the Earth. Volume highlights include: An introduction to the breadth of big earth data analytics Architectures developed to support big earth data analytics Different analysis and statistical methods for big earth data Current applications of analytics to Earth science data Challenges to fully implementing big data analytics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more in this Q&A with the editors. |
| colorado boulder data science: Big Data-Enabled Nursing Connie W. Delaney, Charlotte A. Weaver, Judith J. Warren, Thomas R. Clancy, Roy L. Simpson, 2017-11-02 Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors. |
| colorado boulder data science: Science and Engineering for Grades 6-12 National Academies of Sciences, Engineering, and Medicine, National Academy of Engineering, Division of Behavioral and Social Sciences and Education, Board on Science Education, Committee on Science Investigations and Engineering Design Experiences in Grades 6-12, 2019-03-12 It is essential for today's students to learn about science and engineering in order to make sense of the world around them and participate as informed members of a democratic society. The skills and ways of thinking that are developed and honed through engaging in scientific and engineering endeavors can be used to engage with evidence in making personal decisions, to participate responsibly in civic life, and to improve and maintain the health of the environment, as well as to prepare for careers that use science and technology. The majority of Americans learn most of what they know about science and engineering as middle and high school students. During these years of rapid change for students' knowledge, attitudes, and interests, they can be engaged in learning science and engineering through schoolwork that piques their curiosity about the phenomena around them in ways that are relevant to their local surroundings and to their culture. Many decades of education research provide strong evidence for effective practices in teaching and learning of science and engineering. One of the effective practices that helps students learn is to engage in science investigation and engineering design. Broad implementation of science investigation and engineering design and other evidence-based practices in middle and high schools can help address present-day and future national challenges, including broadening access to science and engineering for communities who have traditionally been underrepresented and improving students' educational and life experiences. Science and Engineering for Grades 6-12: Investigation and Design at the Center revisits America's Lab Report: Investigations in High School Science in order to consider its discussion of laboratory experiences and teacher and school readiness in an updated context. It considers how to engage today's middle and high school students in doing science and engineering through an analysis of evidence and examples. This report provides guidance for teachers, administrators, creators of instructional resources, and leaders in teacher professional learning on how to support students as they make sense of phenomena, gather and analyze data/information, construct explanations and design solutions, and communicate reasoning to self and others during science investigation and engineering design. It also provides guidance to help educators get started with designing, implementing, and assessing investigation and design. |
| colorado boulder data science: Envisioning the Data Science Discipline National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-03-05 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. |
| colorado boulder data science: Report UAG World Data Center A for Solar-Terrestrial Physics, 1972 |
| colorado boulder data science: The Oxford Handbook of Evolution and the Emotions Laith Al-Shawaf, Todd K. Shackelford, 2024-04-25 In this Handbook, Laith Al-Shawaf and Todd K. Shackelford have gathered a group of leading scholars in the field to present a centralized resource for researchers and students wishing to understand emotions from an evolutionary perspective. Experts from a number of different disciplines, including psychology, biology, anthropology, psychiatry, and others, tackle a variety of how (proximate) and why (ultimate) questions about the function of emotions in humans and nonhuman animals, how emotions work, and their place in human life. Comprehensive and integrative in nature, this Handbook is an essential resource for students and scholars from a diversity of fields wishing to build upon their theoretical and empirical understanding of the emotions. |
| colorado boulder data science: 2005 Joint Assembly American Geophysical Union. Joint Assembly, 2005 |
| colorado boulder data science: A Directory of Information Resources in the United States: Physical Sciences, Engineering National Referral Center (U.S.), 1971 |
| colorado boulder data science: Lessons and Legacies of International Polar Year 2007-2008 National Research Council, Division on Earth and Life Studies, Polar Research Board, Committee on the Lessons and Legacies of International Polar Year 2007-2008, 2012-09-08 International Polar Year 2007-2008 (IPY) was an intense, coordinated field campaign of observations, research, and analysis. It was the largest, most comprehensive campaign ever mounted to explore Earth's polar domains. Legacies and Lessons of the International Polar Year 2007-2008 summarizes how IPY engaged the public to communicate the relevance of polar research to the entire planet, strengthened connections with the Indigenous people of the Arctic, and established new observational networks. Legacies and Lessons of the International Polar Year 2007-2008 also addresses the objectives articulated for IPY in the 2004 National Research Council report, A Vision for International Polar Year (NRC, 2004). These objectives include: suggestions for scientific communities and agencies to use the IPY to initiate a sustained effort aimed at assessing large-scale environmental change and variability in the polar regions, the need to explore new scientific frontiers from the molecular to the planetary scale, investment in critical infrastructure and technology to guarantee that IPY 2007-2008 leaves enduring benefits for the nation and for the residents of northern regions, as well as increase public understanding of the importance of polar regions in the global system. Legacies and Lessons of the International Polar Year 2007-2008 explains how activities at both poles led to scientific discoveries that provided a step change in scientific understanding and helped translate scientific knowledge into policy-relevant information. At a time when the polar regions are undergoing a transformation from an icy wilderness to a new zone for human affairs, these insights could not be more timely or more relevant. From outreach activities that engaged the general public to projects that brought researchers from multiple disciplines and several nations together, the legacies of IPY extend far beyond the scientific results achieved, and valuable lessons learned from the process will guide future endeavors of similar magnitude. |
| colorado boulder data science: Telling Stories with Data Rohan Alexander, 2023-07-27 Extensive code examples. Ethics integrated throughout. Reproducibility integrated throughout. Focus on data gathering, messy data, and cleaning data. Extensive formative assessment throughout. |
| colorado boulder data science: Discoverability in Digital Repositories Liz Woolcott, Ali Shiri, 2023-04-04 While most discoverability evaluation studies in the Library and Information Science field discuss the intersection of discovery layers and library systems, this book looks specifically at digital repositories, examining discoverability from the lenses of system structure, user searches, and external discovery avenues. Discoverability, the ease with which information can be found by a user, is the cornerstone of all successful digital information platforms. Yet, most digital repository practitioners and researchers lack a holistic and comprehensive understanding of how and where discoverability happens. This book brings together current understandings of user needs and behaviors and poses them alongside a deeper examination of digital repositories around the theme of discoverability. It examines discoverability in digital repositories from both user and system perspectives by exploring how users access content (including their search patterns and habits, need for digital content, effects of outreach, or integration with Wikipedia and other web-based tools) and how systems support or prevent discoverability through the structure or quality of metadata, system interfaces, exposure to search engines or lack thereof, and integration with library discovery tools. Discoverability in Digital Repositories will be particularly useful to digital repository managers, practitioners, and researchers, metadata librarians, systems librarians, and user studies, usability and user experience librarians. Additionally, and perhaps most prominently, this book is composed with the emerging practitioner in mind. Instructors and students in Library and Information Science and Information Management programs will benefit from this book that specifically addresses discoverability in digital repository systems and services. |
| colorado boulder data science: Summary of Technical Testimony in the Colorado Water Division 1 Trial Nancy D. Gordon, 1995 |
| colorado boulder data science: Smart Energy Practices for a Sustainable World Nina S. Godbole , John P. Lamb , 2023-06-13 Mankind has scaled unprecedented growth since the advent of the Industrial Revolution. However, this progress has come at the hefty cost of environmental degradation. Climate change, undeniably, is one of the biggest challenges of the planet Earth and is largely anthropogenic. In the modern-world context, the phenomenon of climate change is one of the most defining issues, when it comes to realizing objectives of the Sustainable Development Goals (SDGs). Climate change is not limited to geographical boundaries, it is a global problem, hence requires global solutions. It has been widely discussed and therefore has acquired centre stage across the major world forums. Smart Energy Practices for a Sustainable World: how we all can contribute? stresses the need for us to judiciously, sustainably, and smartly harness and use energy techniques in order to effectively combat climate change. The book also gives an in-depth discussion on utilization of artificial intelligence and information technology to realize energy efficiency in various sectors of economy including but not limited to transportation, buildings, infrastructure, health care, and other services. Text is supplemented by case studies that depict ground-level reality to facilitate comprehension of the subject matter. The appendices serve as an extended learning of the concepts discussed in the chapters. The publication would serve as a valuable reference for both scholars and researchers engaged in the domain, in addition to, being a guide to industry as well as the academic world. Table of Contents: 1. Smart, Sustainable, and Green: the mantra to save our planet 2. Smart Energy Systems and Components 3. Energy Production and Delivery 4. Impact of Electronic Equipment on Energy Use and Carbon Footprint 5. Standard Energy Use and Carbon Footprint Metrics 6. Smart Buildings: planning and construction 7. Transport: smarter commuting and energy-efficient mobility 8. Electronic Commerce and Other Digital Services for Smart Planet 9. Sustainable Practices for Green Health Care Services 10. Knowledge and Behaviour for a Smart Planet 11. Energy Audits 12. Worldwide Case Studies for Green Practices 13. The Future for Energy Use in Our Planet Appendices |
| colorado boulder data science: Finding New Ways to Engage and Satisfy Global Customers Patricia Rossi, Nina Krey, 2019-04-01 This proceedings volume explores the new and innovative ways in which marketers find new global customers and build meaningful bridges to them based on their wants and needs in order to ensure high levels of customer satisfaction. Customer loyalty is ensured through continuous engagement with an ever-changing and demanding customer base. Global forces are bringing cultures into collision, creating new challenges for firms wanting to reach geographically and culturally distant markets, and causing marketing managers to rethink how to build meaningful and stable relationships with evermore demanding customers. In an era of vast new data sources and a need for innovative analytics, the challenge for the marketer is to reach customers in new and powerful ways. Featuring the full proceedings from the 2018 Academy of Marketing Science (AMS) World Marketing Congress (WMC) held in Porto, Portugal, this volume provides current and emerging research from global scholars and practitioners that will help marketers to engage and promote customer satisfaction. Founded in 1971, the Academy of Marketing Science is an international organization dedicated to promoting timely explorations of phenomena related to the science of marketing in theory, research, and practice. Among its services to members and the community at large, the Academy offers conferences, congresses, and symposia that attract delegates from around the world. Presentations from these events are published in this Proceedings series, which offers a comprehensive archive of volumes reflecting the evolution of the field. Volumes deliver cutting-edge research and insights, complementing the Academy’s flagship journals, the Journal of the Academy of Marketing Science (JAMS) and AMS Review. Volumes are edited by leading scholars and practitioners across a wide range of subject areas in marketing science. |
| colorado boulder data science: Building Gender Equity in the Academy Sandra Laursen, Ann E. Austin, 2020-11-24 Grounded in scholarship but written for busy institutional leaders, Building Gender Equity in the Academy is a handbook of actionable strategies for faculty and administrators working to improve the inclusion and visibility of women and others who are marginalized in the sciences and in academe more broadly. |
| colorado boulder data science: Big Data Hassan A. Karimi, 2014-02-18 Big data has always been a major challenge in geoinformatics as geospatial data come in various types and formats, new geospatial data are acquired very fast, and geospatial databases are inherently very large. And while there have been advances in hardware and software for handling big data, they often fall short of handling geospatial big data efficiently and effectively. Big Data: Techniques and Technologies in Geoinformatics tackles these challenges head on, integrating coverage of techniques and technologies for storing, managing, and computing geospatial big data. Providing a perspective based on analysis of time, applications, and resources, this book familiarizes readers with geospatial applications that fall under the category of big data. It explores new trends in geospatial data collection, such as geo-crowdsourcing and advanced data collection technologies such as LiDAR point clouds. The book features a range of topics on big data techniques and technologies in geoinformatics including distributed computing, geospatial data analytics, social media, and volunteered geographic information. With chapters contributed by experts in geoinformatics and in domains such as computing and engineering, the book provides an understanding of the challenges and issues of big data in geoinformatics applications. The book is a single collection of current and emerging techniques, technologies, and tools that are needed to collect, analyze, manage, process, and visualize geospatial big data. |
| colorado boulder data science: Report UAG. , 1978 |
| colorado boulder data science: Promoting Black Women's Mental Health Donna Baptiste, Adia Gooden, 2023-04-30 Promoting Black Women's Mental Health celebrates the strengths and complexities of Black women in American life. Many misunderstand and mis-characterize Black women and underappreciate their important contributions to families, communities, and the nation. In this book, a team of Black women mental health practitioners and scholars discuss a range of conditions that impact Black women's self-concepts and mental health. Drawing on a study of Black women across the United States, authors explore the social determinants of Black women's mental health and wellness and Black women's girlhood experiences. The book also explores Black women's stereotypes, their traumas, how they shift in relationships, and images that affect their racial and gender identity development. The book draws on scholarly and popular sources to present Black women's strength and challenges. Authors include commentary, case examples, reflection questions, and resources to improve practitioners' capacities to help Black women clients to recover, heal, and thrive. |
| colorado boulder data science: Social Media and Democracy Nathaniel Persily, Joshua A. Tucker, Joshua Aaron Tucker, 2020-09-03 A state-of-the-art account of what we know and do not know about the effects of digital technology on democracy. |
| colorado boulder data science: Promoting Statistical Practice and Collaboration in Developing Countries O. Olawale Awe, Kim Love, Eric A. Vance, 2022-06-07 Rarely, but just often enough to rebuild hope, something happens to confound my pessimism about the recent unprecedented happenings in the world. This book is the most recent instance, and I think that all its readers will join me in rejoicing at the good it seeks to do. It is an example of the kind of international comity and collaboration that we could and should undertake to solve various societal problems. This book is a beautiful example of the power of the possible. [It] provides a blueprint for how the LISA 2020 model can be replicated in other fields. Civil engineers, or accountants, or nurses, or any other profession could follow this outline to share expertise and build capacity and promote progress in other countries. It also contains some tutorials for statistical literacy across several fields. The details would change, of course, but ideas are durable, and the generalizations seem pretty straightforward. This book shows every other profession where and how to stand in order to move the world. I urge every researcher to get a copy! —David Banks from the Foreword Promoting Statistical Practice and Collaboration in Developing Countries provides new insights into the current issues and opportunities in international statistics education, statistical consulting, and collaboration, particularly in developing countries around the world. The book addresses the topics discussed in individual chapters from the perspectives of the historical context, the present state, and future directions of statistical training and practice, so that readers may fully understand the challenges and opportunities in the field of statistics and data science, especially in developing countries. Features • Reference point on statistical practice in developing countries for researchers, scholars, students, and practitioners • Comprehensive source of state-of-the-art knowledge on creating statistical collaboration laboratories within the field of data science and statistics • Collection of innovative statistical teaching and learning techniques in developing countries Each chapter consists of independent case study contributions on a particular theme that are developed with a common structure and format. The common goal across the chapters is to enhance the exchange of diverse educational and action-oriented information among our intended audiences, which include practitioners, researchers, students, and statistics educators in developing countries. |
| colorado boulder data science: The Elements of Joint Learning and Optimization in Operations Management Xi Chen, Stefanus Jasin, Cong Shi, 2022-09-20 This book examines recent developments in Operations Management, and focuses on four major application areas: dynamic pricing, assortment optimization, supply chain and inventory management, and healthcare operations. Data-driven optimization in which real-time input of data is being used to simultaneously learn the (true) underlying model of a system and optimize its performance, is becoming increasingly important in the last few years, especially with the rise of Big Data. |
| colorado boulder data science: Discrete Diversity and Dispersion Maximization Rafael Martí, Anna Martínez-Gavara, 2024-01-06 This book demonstrates the metaheuristic methodologies that apply to maximum diversity problems to solve them. Maximum diversity problems arise in many practical settings from facility location to social network analysis and constitute an important class of NP-hard problems in combinatorial optimization. In fact, this volume presents a “missing link” in the combinatorial optimization-related literature. In providing the basic principles and fundamental ideas of the most successful methodologies for discrete optimization, this book allows readers to create their own applications for other discrete optimization problems. Additionally, the book is designed to be useful and accessible to researchers and practitioners in management science, industrial engineering, economics, and computer science, while also extending value to non-experts in combinatorial optimization. Owed to the tutorials presented in each chapter, this book may be used in a master course, a doctoral seminar, or as supplementary to a primary text in upper undergraduate courses. The chapters are divided into three main sections. The first section describes a metaheuristic methodology in a tutorial style, offering generic descriptions that, when applied, create an implementation of the methodology for any optimization problem. The second section presents the customization of the methodology to a given diversity problem, showing how to go from theory to application in creating a heuristic. The final part of the chapters is devoted to experimentation, describing the results obtained with the heuristic when solving the diversity problem. Experiments in the book target the so-called MDPLIB set of instances as a benchmark to evaluate the performance of the methods. |
| colorado boulder data science: A Decade of MOOCs and Beyond Irwin King, Wei-I Lee, 2022-12-14 This book is an academic publication about the global development of massive open online courses (MOOCs) and major MOOC platforms worldwide in the past decade, as well as the outlook of MOOCs in the future, with an emphasis on Greater China. The book also discusses the upsurge of the demand for online learning and MOOCs during the COVID-19 pandemic. The book is divided into three main parts - Part I: Overview of MOOCs introduces the origin and history of MOOCs and the development of MOOC platforms in Greater China and the global context; Part II: Key Issues discuss the MOOC policies, innovative pedagogy, technology, and ecosystems worldwide; and Part III: Beyond MOOCs probes into the roles and benefits of MOOCs in times of crises, as well as the outlook of MOOCs in the future. In terms of topic diversity, the book contains a comprehensive investigation of the past and latest MOOC developments, extracting and elaborating on relevant information regarding platforms, policies, pedagogy, technology, and ecosystems. Subsequently, in-depth analyses of MOOC data are utilized to deduce the current trends related to the MOOC movement and to extrapolate the likeliest direction of development for MOOCs in the years to come. The book can inform policymakers, education institutions, course instructors, platform developers, investors, researchers, and individual learners of MOOCs about critical information on the present and future of MOOC development, assisting them in making crucial decisions on what initiatives can optimize their advantages in the sector. |
| colorado boulder data science: Artificial Intelligence for Space: AI4SPACE Matteo Madi, Olga Sokolova, 2023-12-18 The new age space value chain is a complex interconnected system with diverse actors, which involves cross-sector and cross-border collaborations. This book helps to enrich the knowledge of Artificial Intelligence (AI) across the value chain in the space-related domains. Advancements of AI and Machine Learning have impactfully supported the space sector transformation as it is shown in the book. This book embarks on a journey through the fascinating realm of AI in space, exploring its profound implications, emerging trends, and transformative potential. Prof. Dr. Oliver Ullrich - Director Innovation Cluster Space and Aviaton (UZH Space Hub), University of Zurich, Switzerland Aimed at space engineers, risk analysts, policy makers, technical experts and non-specialists, this book demonstrates insights into the implementation of AI in the space sector, alongside its limitations and use-case examples. It covers diverse AI-related topics applicable to space technologies or space big data such as AI-based technologies for improving Earth Observation big data, AI for space robotics exploration, AI for astrophysics, AI for emerging in-orbit servicing market, and AI for space tourism safety improvement. Key Features: Provides an interdisciplinary approach, with chapter contributions from expert teams working in the governmental or private space sectors, with valuable contributions from computer scientists and legal experts Presents insights into AI implementation and how to unlock AI technologies in the field Up-to-date with the latest developments and cutting-edge applications |
| colorado boulder data science: Solanaceae VII: Biology, Genetics, and Evolution Peter Poczai, Nunzio D’Agostino, Rocio Deanna, Ezio Portis, 2023-02-10 |
| colorado boulder data science: NSIDC Notes , 2008 |
| colorado boulder data science: Big Data Analytics for Internet of Things Tausifa Jan Saleem, Mohammad Ahsan Chishti, 2021-03-29 BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies. |
| colorado boulder data science: Learning from the Science of Cognition and Perception for Decision Making National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Behavioral, Cognitive, and Sensory Sciences, 2018-07-29 Beginning in October 2017, the National Academies of Sciences, Engineering, and Medicine organized a set of workshops designed to gather information for the Decadal Survey of Social and Behavioral Sciences for Applications to National Security. The fourth workshop focused on the science of cognition and perception, and this publication summarizes the presentations and discussions from this workshop. |
| colorado boulder data science: Earth System Monitor , 1995 |
| colorado boulder data science: Current and Future Trends in Health and Medical Informatics Kevin Daimi, Abeer Alsadoon, Sara Seabra Dos Reis, 2023-11-01 This book is comprehensive with most of its contents following the recommendations of international health and medical informatics associations and societies. To this extent it covers the areas of healthcare and medical information systems, management of healthcare and medical information systems, healthcare/medical information systems supporting patients and the public, healthcare/medical networking and care sharing, medical imaging and 3D/4D surgical visualization, design and analysis of health/medical records, health/medical data representation and analysis, simulation and modeling in healthcare, and health and medical informatics education. The book provides an excellent professional development resource for educators and practitioners on the state-of-the-art Health and Medical Informatics. It covers many areas and topics of Health and Medical Informatics and contributes toward the enhancement of the community outreach and engagement component of Health and Medical Informatics. Various techniques, methods, and approaches adopted by Health and Medical Informatics experts in the field are introduced. Furthermore, it provides detailed explanation of the Health and Medical Informatics concepts that are aptly reinforced by applications and some practical examples and a road map of future trends that are suitable for innovative Health and Medical Informatics. |
| colorado boulder data science: New Challenges in Space Plasma Physics: Open Questions and Future Mission Concepts Luca Sorriso-Valvo, Alessandro Retino, Christopher H. K. Chen, Daniel Verscharen, 2023-02-15 |
Colorado - Wikipedia
Colorado is noted for its landscape of mountains, forests, high plains, mesas, canyons, plateaus, rivers, and desert lands. It encompasses most of the Southern Rocky Mountains, as well as …
Colorado Tourism - Official Colorado Vacation Guide | Colorado…
From towering mountains and vibrant cities to rich cultural heritage, every part of Colorado offers a unique blend of experiences. Explore the cities below to enjoy the state's diverse activities, …
The 26 Top Things to Do in Colorado, According to a Local
Mar 17, 2025 · Planning a trip to Colorado? From hiking in the Rocky Mountains to skiing in Aspen to staying in a haunted hotel, here are the top things to do in Colorado.
Colorado | Flag, Facts, Maps, & Points of Interest | Britannica
4 days ago · Geographical and historical treatment of Colorado, including maps and a survey of its people, economy, and government. Colorado’s history is written in the names of its cities, …
Colorado: An Overview - Colorado Encyclopedia
Colorado, “the Centennial State,” was the thirty-eighth state to enter the Union on August 1, 1876. Its diverse geography encompasses 104,094 square miles of the American West and includes …
Visitors - Colorado.gov
Plan your Colorado vacation now and find out if you're Colo-Ready! Find the exact park facilities or activities that you're looking for. Find Your Next Adventure! Traveler information for …
Anti-Trump 'No Kings' protests planned across Colorado - The …
2 days ago · Colorado’s rallies are being held as part of a national effort to turn out large crowds in cities and towns across America. “They’ve defied our courts, deported Americans, …
Your ultimate guide to Colorado - Time Out
Colorado is packed with great things to do and places to go. But where do you begin? Cut through the noise with Time Out’s recommendations of the best attractions, restaurants, bars, nightlife...
Colorado Maps & Facts - World Atlas
May 21, 2024 · Colorado is a landlocked state located in the central United States. It borders Kansas in the east, Utah in the west, Arizona in the southwest, Nebraska and Wyoming in the …
18 Best Places to Visit in Colorado | U.S. News Travel
Sep 18, 2024 · From the magical Rocky Mountain National Park to lesser-known mining towns, this list of the best places to visit in Colorado showcases the best the state has to offer.
Colorado - Wikipedia
Colorado is noted for its landscape of mountains, forests, high plains, mesas, canyons, plateaus, rivers, and desert lands. It encompasses most of the Southern Rocky Mountains, as well as …
Colorado Tourism - Official Colorado Vacation Guide | Colorado…
From towering mountains and vibrant cities to rich cultural heritage, every part of Colorado offers a unique blend of experiences. Explore the cities below to enjoy the state's diverse activities, …
The 26 Top Things to Do in Colorado, According to a Local
Mar 17, 2025 · Planning a trip to Colorado? From hiking in the Rocky Mountains to skiing in Aspen to staying in a haunted hotel, here are the top things to do in Colorado.
Colorado | Flag, Facts, Maps, & Points of Interest | Britannica
4 days ago · Geographical and historical treatment of Colorado, including maps and a survey of its people, economy, and government. Colorado’s history is written in the names of its cities, …
Colorado: An Overview - Colorado Encyclopedia
Colorado, “the Centennial State,” was the thirty-eighth state to enter the Union on August 1, 1876. Its diverse geography encompasses 104,094 square miles of the American West and includes …
Visitors - Colorado.gov
Plan your Colorado vacation now and find out if you're Colo-Ready! Find the exact park facilities or activities that you're looking for. Find Your Next Adventure! Traveler information for …
Anti-Trump 'No Kings' protests planned across Colorado - The …
2 days ago · Colorado’s rallies are being held as part of a national effort to turn out large crowds in cities and towns across America. “They’ve defied our courts, deported Americans, …
Your ultimate guide to Colorado - Time Out
Colorado is packed with great things to do and places to go. But where do you begin? Cut through the noise with Time Out’s recommendations of the best attractions, restaurants, bars, nightlife...
Colorado Maps & Facts - World Atlas
May 21, 2024 · Colorado is a landlocked state located in the central United States. It borders Kansas in the east, Utah in the west, Arizona in the southwest, Nebraska and Wyoming in the …
18 Best Places to Visit in Colorado | U.S. News Travel
Sep 18, 2024 · From the magical Rocky Mountain National Park to lesser-known mining towns, this list of the best places to visit in Colorado showcases the best the state has to offer.
