Author: Shane Safir Publisher: Corwin ISBN: 1071812661 Category : Education Languages : en Pages : 281
Book Description
Radically reimagine our ways of being, learning, and doing Education can be transformed if we eradicate our fixation on big data like standardized test scores as the supreme measure of equity and learning. Instead of the focus being on "fixing" and "filling" academic gaps, we must envision and rebuild the system from the student up—with classrooms, schools and systems built around students’ brilliance, cultural wealth, and intellectual potential. Street data reminds us that what is measurable is not the same as what is valuable and that data can be humanizing, liberatory and healing. By breaking down street data fundamentals: what it is, how to gather it, and how it can complement other forms of data to guide a school or district’s equity journey, Safir and Dugan offer an actionable framework for school transformation. Written for educators and policymakers, this book · Offers fresh ideas and innovative tools to apply immediately · Provides an asset-based model to help educators look for what’s right in our students and communities instead of seeking what’s wrong · Explores a different application of data, from its capacity to help us diagnose root causes of inequity, to its potential to transform learning, and its power to reshape adult culture Now is the time to take an antiracist stance, interrogate our assumptions about knowledge, measurement, and what really matters when it comes to educating young people.
Author: Ulrika Jägare Publisher: John Wiley & Sons ISBN: 1119566274 Category : Computers Languages : en Pages : 423
Book Description
All the answers to your data science questions Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the “what” and the “why” of data science and covering what it takes to lead and nurture a top-notch team of data scientists. With this book, you’ll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data. Learn exactly what data science is and why it’s important Adopt a data-driven mindset as the foundation to success Understand the processes and common roadblocks behind data science Keep your data science program focused on generating business value Nurture a top-quality data science team In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value.
Author: Nick Salafsky Publisher: Island Press ISBN: 1642831352 Category : Nature Languages : en Pages : 330
Book Description
As environmental problems grow larger and more pressing, conservation work has increasingly emphasized broad approaches to combat global-scale crises of biodiversity loss, invasive species, and climate change. Pathways to Success is a modern guide to building large-scale transformative conservation programs capable of tackling the complex issues we now face. In this strikingly illustrated volume, coauthors Nick Salafsky and Richard Margoluis walk readers through fundamental concepts of effective program-level design, helping them to think strategically about project coordination, funding, and stakeholder input. Pathways to Success is the definitive guide for conservation program managers and funders who want to increase the effectiveness of their work combating climate change, species extinctions, and the many challenges we face to keep our planet livable.
Author: National Academies of Sciences, Engineering, and Medicine Publisher: National Academies Press ISBN: 0309475597 Category : Education Languages : en Pages : 139
Book Description
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.
Author: Jerry W. Hedge Publisher: ISBN: 0190907789 Category : Business & Economics Languages : en Pages : 373
Book Description
"Major changes have occurred in the workplace during the last several decades that have transformed the nature of work, and our preparation for work. In recent years, we have seen the globalization of thousands of companies and most industries, organizational downsizing and restructuring, greater use of information technology at work, changes in work contracts, and the growth of various alternative education and work strategies and schedules"--
Author: Avrim Blum Publisher: Cambridge University Press ISBN: 1108617360 Category : Computers Languages : en Pages : 433
Book Description
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author: Mark L. Gillenson Publisher: John Wiley & Sons ISBN: 0470101865 Category : Computers Languages : en Pages : 1011
Book Description
You can get there Where do you want to go? You might already be working in the information technology field and may be looking to expand your skills. You might be setting out on a new career path. Or, you might want to learn more about exciting opportunities in database management. Wherever you want to go, Introduction to Databases will help you get there. Easy-to-read, practical, and up-to-date, this text not only helps you learn fundamental database design and management concepts, it also helps you master the core competencies and skills you need to succeed in the classroom and in the real world. The book's brief, modular format and variety of built-in learning resources enable you to learn at your own pace and focus your studies. With this book, you will be able to: * Appreciate the key role of data in daily business operations and strategic decisions. * Understand databases, database management systems, and SQL, the software on which they are based, from the ground up. * Know how to gather and organize critical business information, design a database based on this information, and retrieve and modify that information in a useful manner. * Use accepted data modeling procedures to design a relational database. * Master the concept of data normalization and the use of standard normalization rules. * Explore critical real-world issues including application integration and securing data against disclosure and loss. Wiley Pathways helps you achieve your goals Not every student is on the same path, but every student wants to succeed. The Information Technology series in the new Wiley Pathways imprint helps you achieve your goals. The books in this series--Introduction to Databases, Introduction to Programming Using Visual Basic, Introduction to Operating Systems, Networking Basics, Windows Network Administration, Network Security Fundamentals, and PC Hardware Essentials--offer a coordinated information technology curriculum. Learn more at www.wiley.com/go/pathways
Author: Nenad Blau Publisher: Springer ISBN: 3642403379 Category : Medical Languages : en Pages : 880
Book Description
This book, combining and updating two previous editions, is a unique source of information on the diagnosis, treatment, and follow-up of metabolic diseases. The clinical and laboratory data characteristic of rare metabolic conditions can be bewildering for both clinicians and laboratory personnel. Reference laboratory data are scattered, and clinical descriptions may be obscure. The Physician’s Guide documents the features of more than five hundred conditions, grouped according to type of disorder, organ system affected (e.g. liver, kidney, etc) or phenotype (e.g. neurological, hepatic, etc). Relevant clinical findings are provided and pathological values for diagnostic metabolites highlighted. Guidance on appropriate biochemical genetic testing is provided. Established experimental therapeutic protocols are described, with recommendations on follow-up and monitoring. The authors are acknowledged experts, and the book will be a valuable desk reference for all who deal with inherited metabolic diseases.
Author: Amy L. Affelt Publisher: Information Today ISBN: 9781573875110 Category : Big data Languages : en Pages : 0
Book Description
Amy Affelt, author of The Accidental Data Scientist, notes that "Librarians and information professionals have always worked with data in order to meet the information needs of their constituents, thus 'Big Data' is not a new concept for them." With The Accidental Data Scientist, Amy Affelt shows information professionals how to leverage their skills and training to master emerging tools, techniques, and vocabulary; create mission-critical Big Data research deliverables; and discover rewarding new career opportunities by embracing their inner Data Scientist.
Author: Wes McKinney Publisher: "O'Reilly Media, Inc." ISBN: 1491957611 Category : Computers Languages : en Pages : 553
Book Description
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Author: Shane Safir
Author: Ulrika Jägare
Author: Nick Salafsky
Author: National Academies of Sciences, Engineering, and Medicine
Author: Jerry W. Hedge
Author: Avrim Blum
Author: Mark L. Gillenson
Author: Nenad Blau
Author: Amy L. Affelt
Author: Wes McKinney