Download or read book Data Science Thinking written by Longbing Cao and published by Springer. This book was released on 2018-08-17 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Teaching Science Thinking written by Christopher Moore and published by Routledge. This book was released on 2018-11-08 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Teach your students how to think like scientists. This book shows you practical ways to incorporate science thinking in your classroom using simple "Thinking Tasks" that you can insert into any lesson. What is science thinking and how can you possibly teach and assess it? How is science thinking incorporated into the Next Generation Science Standards (NGSS) and how can it be weaved into your curriculum? This book answers these questions. This practical book provides a clear, research-verified framework for helping students develop scientific thinking as required by the NGSS. Your students will not be memorizing content but will become engaged in the real work scientists do, using critical thinking patterns such as: Recognizing patterns, Inventing new hypotheses based on observations, Separating causes from correlations, Determining relevant variables and isolating them, Testing hypotheses, and Thinking about their own thinking and the relative value of evidence. The book includes a variety of sample classroom activities and rubrics, as well as frameworks for creating your own tools. Designed for the busy teacher, this book also shows you quick and simple ways to add deep science thinking to existing lessons.

Download or read book Ethical Data Science written by Anne L. Washington and published by Oxford University Press. This book was released on 2023 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can data science truly serve the public interest? Data-driven analysis shapes many interpersonal, consumer, and cultural experiences yet scientific solutions to social problems routinely stumble. All too often, predictions remain solely a technocratic instrument that sets financial interests against service to humanity. Amidst a growing movement to use science for positive change, Anne L. Washington offers a solution-oriented approach to the ethical challenges of data science. Ethical Data Science empowers those striving to create predictive data technologies that benefit more people. As one of the first books on public interest technology, it provides a starting point for anyone who wants human values to counterbalance the institutional incentives that drive computational prediction. It argues that data science prediction embeds administrative preferences that often ignore the disenfranchised. The book introduces the prediction supply chain to highlight moral questions alongside the interlocking legal and commercial interests influencing data science. Structured around a typical data science workflow, the book systematically outlines the potential for more nuanced approaches to transforming data into meaningful patterns. Drawing on arts and humanities methods, it encourages readers to think critically about the full human potential of data science step-by-step. Situating data science within multiple layers of effort exposes dependencies while also pinpointing opportunities for research ethics and policy interventions. This approachable process lays the foundation for broader conversations with a wide range of audiences. Practitioners, academics, students, policy makers, and legislators can all learn how to identify social dynamics in data trends, reflect on ethical questions, and deliberate over solutions. The book proves the limits of predictive technology controlled by the few and calls for more inclusive data science.

Download or read book The Data Science Design Manual written by Steven S. Skiena and published by Springer. This book was released on 2017-07-01 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)

Download or read book Roundtable on Data Science Postsecondary Education written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-09-02 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Applied Data Science in Tourism written by Roman Egger and published by Springer Nature. This book was released on 2022-01-31 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau

Download or read book Learning Data Science written by Sam Lau and published by "O'Reilly Media, Inc.". This book was released on 2023-09-15 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. Refine a question of interest to one that can be studied with data Pursue data collection that may involve text processing, web scraping, etc. Glean valuable insights about data through data cleaning, exploration, and visualization Learn how to use modeling to describe the data Generalize findings beyond the data

Download or read book Design Thinking for Software Engineering written by Jennifer Hehn and published by Springer Nature. This book was released on 2022-02-13 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the possibility of integrating design thinking into today’s technical contexts. Despite the popularity of design thinking in research and practice, this area is still too often treated in isolation without a clear, consistent connection to the world of software development. The book presents design thinking approaches and experiences that can facilitate the development of software-intensive products and services. It argues that design thinking and related software engineering practices, including requirements engineering and user-centric design (UX) approaches, are not mutually exclusive. Rather, they provide complementary methods and tools for designing software-intensive systems with a human-centric approach. Bringing together prominent experts and practitioners to share their insights, approaches and experiences, the book sheds new light on the specific interpretations and meanings of design thinking in various fields such as engineering, management, and information technology. As such, it provides a framework for professionals to demonstrate the potential of design thinking for software development, while offering academic researchers a roadmap for further research.

Download or read book An Invitation to Cognitive Science Thinking written by Daniel N. Osherson and published by MIT Press. This book was released on 1995 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rather than surveying theories and data in the manner characteristic of many introductory textbooks in the field, An Invitation to Cognitive Science employs a unique case study approach, presenting a focused research topic in some depth and relying on suggested readings to convey the breadth of views and results.

Download or read book An Introduction to Data Science With Python written by Jeffrey S. Saltz and published by SAGE Publications. This book was released on 2024-05-29 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Data Science with Python by Jeffrey S. Saltz and Jeffery M. Stanton provides readers who are new to Python and data science with a step-by-step walkthrough of the tools and techniques used to analyze data and generate predictive models. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using Python-based Jupyter Notebooks. The techniques include making tables and data frames, computing statistics, managing data, creating data visualizations, and building machine learning models. Each chapter breaks down the process into simple steps and components so students with no more than a high school algebra background will still find the concepts and code intelligible. Explanations are reinforced with linked practice questions throughout to check reader understanding. The book also covers advanced topics such as neural networks and deep learning, the basis of many recent and startling advances in machine learning and artificial intelligence. With their trademark humor and clear explanations, Saltz and Stanton provide a gentle introduction to this powerful data science tool. Included with this title: LMS Cartridge: Import this title’s instructor resources into your school’s learning management system (LMS) and save time. Don′t use an LMS? You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.

Download or read book Big Data MBA written by Bill Schmarzo and published by John Wiley & Sons. This book was released on 2015-12-11 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.

Download or read book Design Thinking and Innovation Metrics written by Michael Lewrick and published by John Wiley & Sons. This book was released on 2023-04-11 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create, manage, and measure innovation In Design Thinking and Innovation Metrics: Powerful Tools to Manage Creativity, OKRs, Product, and Business Success, bestselling author Michael Lewrick delivers a simple and straightforward playbook to manage and measure innovation. In the book, you’ll learn how to utilize the design thinking paradigm for innovation success and how successful leaders manage Explore and Exploit portfolios to create impact. The author explains how to: Strategically employ data analytics, artificial intelligence, and neurodesign to drive innovation and business results Deploy Objectives and Key Results (OKRs) for innovation teams to realize true alignment between the business and team performance Use the provided hands-on tools to measure your firm’s success at creating meaningfully new and interesting products, services, and experiences Part of the Design Thinking Series, Design Thinking and Innovation Metrics will earn a place in the libraries of managers, executives, product owners, innovation teams, entrepreneurs, and other business leaders.

Download or read book New Statistical Developments in Data Science written by Alessandra Petrucci and published by Springer Nature. This book was released on 2019-08-20 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects the extended versions of papers presented at the SIS Conference “Statistics and Data Science: new challenges, new generations”, held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science, the contributions offer an essential overview of the latest developments in various areas of statistics research. The 35 contributions have been divided into six parts, each of which focuses on a core area contributing to “Data Science”. The book covers topics including strong statistical methodologies, Bayesian approaches, applications in population and social studies, studies in economics and finance, techniques of sample design and mathematical statistics. Though the book is mainly intended for researchers interested in the latest frontiers of Statistics and Data Analysis, it also offers valuable supplementary material for students of the disciplines dealt with here. Lastly, it will help Statisticians and Data Scientists recognize their counterparts’ fundamental role.

Download or read book Ethnography for a data saturated world written by Hannah Knox and published by Manchester University Press. This book was released on 2018-10-03 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited collection aims to reimagine and extend ethnography for a data-saturated world. The book brings together leading scholars in the social sciences who have been interrogating and collaborating with data scientists working in a range of different settings. The book explores how a repurposed form of ethnography might illuminate the kinds of knowledge that are being produced by data science. It also describes how collaborations between ethnographers and data scientists might lead to new forms of social analysis

Download or read book Big Data Science and Analytics for Smart Sustainable Urbanism written by Simon Elias Bibri and published by Springer. This book was released on 2019-05-30 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holistic and integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.

Download or read book Using Science to Develop Thinking Skills at Key Stage 3 written by Pat O'Brien and published by Routledge. This book was released on 2013-01-11 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a series of practical activities designed to help teachers build an effective science curriculum for more able children. It focuses on: developing higher order thinking skills using conceptual language; directed activities relating to text for developing higher order skills; and in-depth study topics that emphasize a "real product" outcome.

Download or read book Trends in Teaching Experimentation in the Life Sciences written by Nancy J. Pelaez and published by Springer Nature. This book was released on 2022-05-11 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a guide for educators on how to develop and evaluate evidence-based strategies for teaching biological experimentation to thereby improve existing and develop new curricula. It unveils the flawed assumptions made at the classroom, department, and institutional level about what students are learning and what help they might need to develop competence in biological experimentation. Specific case studies illustrate a comprehensive list of key scientific competencies that unpack what it means to be a competent experimental life scientist. It includes explicit evidence-based guidelines for educators regarding the teaching, learning, and assessment of biological research competencies. The book also provides practical teacher guides and exemplars of assignments and assessments. It contains a complete analysis of the variety of tools developed thus far to assess learning in this domain. This book contributes to the growth of public understanding of biological issues including scientific literacy and the crucial importance of evidence-based decision-making around public policy. It will be beneficial to life science instructors, biology education researchers and science administrators who aim to improve teaching in life science departments. Chapters 6, 12, 14 and 22 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.