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Multimedia in the College Classroom: Improve Learning and Connect with Students in Online and Hybrid Courses
by Heidi Skurat Harris Michael GreerThis practical guide to multimedia in online college instruction provides easy-to-follow instructions for designing multimedia assignments that maximize student learning while reducing cognitive load.This book presents the learning process as a complex, multidimensional experience that includes texts as well as auditory and visual elements. Each chapter includes research-based activities to develop instructors’ multimedia skills. The book leverages cutting edge cognitive research to improve accessibility and design, while also providing practical asynchronous and synchronous activities that engage learners.Multimedia in the College Classroom is the ideal resource for any higher education instructor, administrator, or leader who wishes to learn about, reflect on, and implement research-based learning strategies through the targeted use of multimedia.
Multimedia in the College Classroom: Improve Learning and Connect with Students in Online and Hybrid Courses
by Heidi Skurat Harris Michael GreerThis practical guide to multimedia in online college instruction provides easy-to-follow instructions for designing multimedia assignments that maximize student learning while reducing cognitive load.This book presents the learning process as a complex, multidimensional experience that includes texts as well as auditory and visual elements. Each chapter includes research-based activities to develop instructors’ multimedia skills. The book leverages cutting edge cognitive research to improve accessibility and design, while also providing practical asynchronous and synchronous activities that engage learners.Multimedia in the College Classroom is the ideal resource for any higher education instructor, administrator, or leader who wishes to learn about, reflect on, and implement research-based learning strategies through the targeted use of multimedia.
From Concepts to Code: Introduction to Data Science
by Adam P. TashmanThe breadth of problems that can be solved with data science is astonishing, and this book provides the required tools and skills fot a broad audience. The reader takes a journey into the forms, uses, and abuses of data and models, and learns how to critically examine each step. Python coding and data analysis skills are built from the ground up, with no prior coding experience assumed. The necessary background in computer science, mathematics, and statistics is provided in an approachable manner.Each step of the machine learning lifecycle is discussed, from business objective planning to monitoring a model in production. This end-to-end approach supplies the broad view necessary to sidestep many of the pitfalls that can sink a data science project. Detailed examples are provided from a wide range of applications and fields, from fraud detection in banking to breast cancer classification in healthcare. The reader will learn the techniques to accomplish tasks that include predicting outcomes, explaining observations, and detecting patterns. Improper use of data and models can introduce unwanted effects and dangers to society. A chapter on model risk provides a framework for comprehensively challenging a model and mitigating weaknesses. When data is collected, stored, and used, it may misrepresent reality and introduce bias. Strategies for addressing bias are discussed. From Concepts to Code: Introduction to Data Science leverages content developed by the author for a full-year data science course suitable for advanced high school or early undergraduate students. This course is freely available and it includes weekly lesson plans.
From Concepts to Code: Introduction to Data Science
by Adam P. TashmanThe breadth of problems that can be solved with data science is astonishing, and this book provides the required tools and skills fot a broad audience. The reader takes a journey into the forms, uses, and abuses of data and models, and learns how to critically examine each step. Python coding and data analysis skills are built from the ground up, with no prior coding experience assumed. The necessary background in computer science, mathematics, and statistics is provided in an approachable manner.Each step of the machine learning lifecycle is discussed, from business objective planning to monitoring a model in production. This end-to-end approach supplies the broad view necessary to sidestep many of the pitfalls that can sink a data science project. Detailed examples are provided from a wide range of applications and fields, from fraud detection in banking to breast cancer classification in healthcare. The reader will learn the techniques to accomplish tasks that include predicting outcomes, explaining observations, and detecting patterns. Improper use of data and models can introduce unwanted effects and dangers to society. A chapter on model risk provides a framework for comprehensively challenging a model and mitigating weaknesses. When data is collected, stored, and used, it may misrepresent reality and introduce bias. Strategies for addressing bias are discussed. From Concepts to Code: Introduction to Data Science leverages content developed by the author for a full-year data science course suitable for advanced high school or early undergraduate students. This course is freely available and it includes weekly lesson plans.
Artificial Intelligence Law
by Edward SwanIt is inevitable, given the enormous media-driven concern generated by the recent application of artificial intelligence (AI) to an ever-expanding spectrum of day-to-day human experience, that the need for a clearly articulated legal response has become imperative. This book both clarifies the controversial issues surrounding the use of AI and explores in great detail how, far from being “unregulated,” the creation, distribution, and operation of AI systems currently is, and will remain, subject to a vast array of existing laws and regulations all over the world. Demonstrating beyond any doubt that the traditional concepts of legal responsibility, including duty of care, negligence, and compensation for damages, will always be applicable to those humans who create and/or use artificially intelligent things or systems, the author shows how AI systems are clearly implicated in numerous existing legal regimes, including the following: relevant provisions under international law and EU law; applicable provisions in the laws of the United States, the United Kingdom, France, China, India, Japan, South Korea, and Singapore; and numerous national provisions in the legal fields of health and safety, intellectual property, competition, privacy and data protection, and military engagement. However, given the lack of international consensus on this vitally important issue, the author suggests that any worldwide agreement on the legal responsibilities relating to the use of AI will need to be carefully defined, and that provisions will need to be reviewed to determine how they will apply to any new range of artificially intelligent creations. The purpose of this book is to review those legal concepts, throughout the world, that currently govern the application of AI and to comment on modifications or extensions of the rule of law that are being proposed as necessary to serve and protect humanity in relation to the expanding applications of AI. It is important that anyone who uses or is affected by AI products understands the relationship between existing laws and regulations in major markets around the world and those areas where initial regulations may be required. For them, for their counsel, and for the various policy and regulatory authorities confronted with AI issues, this book will prove an essential guide.
Digital Forensics and Watermarking: 22nd International Workshop, IWDW 2023, Jinan, China, November 25–26, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14511)
by Bin Ma Jian Li Qi LiThis book constitutes the refereed post proceedings of the 22nd International Workshop on Digital Forensics and Watermarking, IWDW 2023, held in Jinan, China, during November 25–26, 2023. The 22 full papers included in this book were carefully reviewed and selected from 48 submissions. The workshop focuses on subjects such as novel research, development and application of digital watermarking, data hiding, and forensic techniques for multimedia security.
Proceedings of the 2nd International Conference on Big Data, IoT and Machine Learning: BIM 2023 (Lecture Notes in Networks and Systems #867)
by Mohammad Shamsul Arefin M. Shamim Kaiser Touhid Bhuiyan Nilanjan Dey Mufti MahmudThis book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2023), organised by Jahangirnagar University, Bangladesh, and Daffodil International University, Bangladesh, held in Dhaka, Bangladesh, during 6–8 September 2023. The book covers research papers in the field of big data, IoT and machine learning. The book is helpful for active researchers and practitioners in the field.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part III (Lecture Notes in Computer Science #14647)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
The Second International Adaptive and Sustainable Science, Engineering and Technology Conference: ASSET 2023 Proceedings (Signals and Communication Technology)
by Sunday Cookey EkpoThis proceedings presents papers from the Second International Adaptive and Sustainable Science, Engineering and Technology Conference (ASSET 2023), which took place simultaneously in Manchester, UK and Ikot Akpaden, Nigeria on 18-20, July 2023. The ASSET conference serves as an interactive forum for the advancement of the practice of adaptive and sustainable systems across the multiple disciplines and specialty areas involved with the science, engineering, and technology of integrated entities, complex systems, and networks. The conference provides an avenue for practitioners, researchers, managers, developers, analysts, educators, and users to exchange innovative ideas, concepts, applications, and lessons learned in addressing domain-specific problems, applications-oriented topics, methodologies, standards and multidisciplinary research opportunities and findings relating to ASSET systems.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part I (Lecture Notes in Computer Science #14645)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Industrial Engineering in the Sustainability Era: Selected Papers from the Hybrid Global Joint Conference on Industrial Engineering and Its Application Areas, GJCIE 2023, August 14–16, 2023, New York, USA (Lecture Notes in Management and Industrial Engineering)
by Fethi Calisir Mohammad T. Khasawneh Murat DurucuThis book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), held on August 14-16, 2023, in New York, USA. Continuing the tradition of previous volumes, it highlights recent developments of industrial engineering and digital and intelligent technologies for improving manufacturing processes, and healthcare and transportation services, among others applications. A special emphasis is given to engineering methods and strategies fostering a sustainable business development.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part V (Lecture Notes in Computer Science #14649)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part II (Lecture Notes in Computer Science #14646)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Advances in Knowledge Discovery and Data Mining: 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7–10, 2024, Proceedings, Part VI (Lecture Notes in Computer Science #14650)
by De-Nian Yang Xing Xie Vincent S. Tseng Jian Pei Jen-Wei Huang Jerry Chun-Wei LinThe 6-volume set LNAI 14645-14650 constitutes the proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, which took place in Taipei, Taiwan, during May 7–10, 2024. The 177 papers presented in these proceedings were carefully reviewed and selected from 720 submissions. They deal with new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, big data technologies, and foundations.
Threat Modeling: Designing for Security
by Adam ShostackThe only security book to be chosen as a Dr. Dobbs Jolt Award Finalist since Bruce Schneier's Secrets and Lies and Applied Cryptography!Adam Shostack is responsible for security development lifecycle threat modeling at Microsoft and is one of a handful of threat modeling experts in the world. Now, he is sharing his considerable expertise into this unique book. With pages of specific actionable advice, he details how to build better security into the design of systems, software, or services from the outset. You'll explore various threat modeling approaches, find out how to test your designs against threats, and learn effective ways to address threats that have been validated at Microsoft and other top companies. Systems security managers, you'll find tools and a framework for structured thinking about what can go wrong. Software developers, you'll appreciate the jargon-free and accessible introduction to this essential skill. Security professionals, you'll learn to discern changing threats and discover the easiest ways to adopt a structured approach to threat modeling. Provides a unique how-to for security and software developers who need to design secure products and systems and test their designs Explains how to threat model and explores various threat modeling approaches, such as asset-centric, attacker-centric and software-centric Provides effective approaches and techniques that have been proven at Microsoft and elsewhere Offers actionable how-to advice not tied to any specific software, operating system, or programming language Authored by a Microsoft professional who is one of the most prominent threat modeling experts in the world As more software is delivered on the Internet or operates on Internet-connected devices, the design of secure software is absolutely critical. Make sure you're ready with Threat Modeling: Designing for Security.
Artificial Intelligence in Music, Sound, Art and Design: 13th International Conference, EvoMUSART 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings (Lecture Notes in Computer Science #14633)
by Colin Johnson Sérgio M. Rebelo Iria SantosThis book constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2024, held as part of EvoStar 2024, in Aberystwyth, UK, April 3–5, 2024. The 17 full papers and 8 short papers presented in this book were carefully reviewed and selected from 55 submissions. The main purpose of this conference proceedings was to bring together practitioners who are using Artificial Intelligence techniques for artistic tasks, providing the opportunity to promote, present, and discuss ongoing work in the area.
Model-Driven Software Systems Development Using the Meta-Artifact Process
by Wayne O'BrienThe importance of architecture for software systems is widely accepted, but the role of architecture in the overall development process is not so clear. Presenting an architecture-centric process, Model-Driven Software Systems Development Using the Meta-Artifact Process makes the role of architecture clear. At its core, this book is about developing software systems and, more specifically, software code. It describes three major innovations for making software, which are combined with five widely used enabling technologies, to provide a complete, hypothesis-driven software development process known as Meta-Artifact Process (MAP). Having complete requirements is essential for making good software and supports the hypothesis-driven MAP.MAP offers properties, qualities, and capabilities that help stakeholders and developers understand and reason about a domain and target systems of interest. MAP, through the central role of the Meta-Artifact and incorporating the view that a computer program is a hypothesis about the requirements, offers new ways to look at systems and their development, even changing the roles of developers and stakeholders.Recommending agile methods wherever appropriate while supporting the OMG Essence standard and working within an overarching architecture, MAP presents ways to ensure that the requirements are complete and correct. It helps to identify likely points during development to form alternative hypotheses about them. Because MAP requires an underlying software development process, it can provide that clarity to existing processes in which the organization’s developers are already proficient.This book provides concrete examples from two broad but diverse areas—Accounting Information Systems in the commercial area and a military command and control system—to show the wide applicability of MAP in both commercial and defense domains.
Model-Driven Software Systems Development Using the Meta-Artifact Process
by Wayne O'BrienThe importance of architecture for software systems is widely accepted, but the role of architecture in the overall development process is not so clear. Presenting an architecture-centric process, Model-Driven Software Systems Development Using the Meta-Artifact Process makes the role of architecture clear. At its core, this book is about developing software systems and, more specifically, software code. It describes three major innovations for making software, which are combined with five widely used enabling technologies, to provide a complete, hypothesis-driven software development process known as Meta-Artifact Process (MAP). Having complete requirements is essential for making good software and supports the hypothesis-driven MAP.MAP offers properties, qualities, and capabilities that help stakeholders and developers understand and reason about a domain and target systems of interest. MAP, through the central role of the Meta-Artifact and incorporating the view that a computer program is a hypothesis about the requirements, offers new ways to look at systems and their development, even changing the roles of developers and stakeholders.Recommending agile methods wherever appropriate while supporting the OMG Essence standard and working within an overarching architecture, MAP presents ways to ensure that the requirements are complete and correct. It helps to identify likely points during development to form alternative hypotheses about them. Because MAP requires an underlying software development process, it can provide that clarity to existing processes in which the organization’s developers are already proficient.This book provides concrete examples from two broad but diverse areas—Accounting Information Systems in the commercial area and a military command and control system—to show the wide applicability of MAP in both commercial and defense domains.
Advancement of Data Processing Methods for Artificial and Computing Intelligence (River Publishers Series in Computing and Information Science and Technology)
by Seema Rawat V. Ajantha Devi Praveen KumarThis book emphasizes the applications of advances in data processing methods for Artificial Intelligence in today's fast-changing world, as well as to serve society through research, innovation, and development in this field. This book is applicable to a wide range of data that contribute to data science concerns and can be used to promote research in this high-potential new field. People's perceptions of the world and how they conduct their lives have changed dramatically as a result of technological advancements. The world has been gripped by technology, and the advances that are being made every day are undeniably transforming the planet. In the domains of Big Data, engineering, and data science, this cutting-edge technology is ready to support us.Artificial intelligence (AI) is a current research topic because it can be applied to a wide range of applications and disciplines to solve complicated problems and find optimal solutions. In research, medicine, technology, and the social sciences, the benefits of AI have already been proven. Data science, also known as pattern analytics and mining, is a technique for extracting useful and relevant information from databases, enabling better decision-making and strategy formulation in a range of fields. As a result of the exponential growth of data in recent years, the combined notions of big data and AI have given rise to many study areas, such as scale-up behaviour from classical algorithms. Furthermore, combining numerous AI technologies from other areas (such as vision, security, control, and biology) in order to build efficient and durable systems that interact in the real world is a new problem. Despite recent improvements in fundamental AI technologies, the integration of these skills into larger, trustworthy, transparent, and maintainable systems is still in its development. Both conceptually and practically, there are a number of unanswered issues.
Advancement of Data Processing Methods for Artificial and Computing Intelligence (River Publishers Series in Computing and Information Science and Technology)
This book emphasizes the applications of advances in data processing methods for Artificial Intelligence in today's fast-changing world, as well as to serve society through research, innovation, and development in this field. This book is applicable to a wide range of data that contribute to data science concerns and can be used to promote research in this high-potential new field. People's perceptions of the world and how they conduct their lives have changed dramatically as a result of technological advancements. The world has been gripped by technology, and the advances that are being made every day are undeniably transforming the planet. In the domains of Big Data, engineering, and data science, this cutting-edge technology is ready to support us.Artificial intelligence (AI) is a current research topic because it can be applied to a wide range of applications and disciplines to solve complicated problems and find optimal solutions. In research, medicine, technology, and the social sciences, the benefits of AI have already been proven. Data science, also known as pattern analytics and mining, is a technique for extracting useful and relevant information from databases, enabling better decision-making and strategy formulation in a range of fields. As a result of the exponential growth of data in recent years, the combined notions of big data and AI have given rise to many study areas, such as scale-up behaviour from classical algorithms. Furthermore, combining numerous AI technologies from other areas (such as vision, security, control, and biology) in order to build efficient and durable systems that interact in the real world is a new problem. Despite recent improvements in fundamental AI technologies, the integration of these skills into larger, trustworthy, transparent, and maintainable systems is still in its development. Both conceptually and practically, there are a number of unanswered issues.
Transformative AI: Responsible, Transparent, and Trustworthy AI systems (River Publishers Series in Computing and Information Science and Technology)
by Ahmed BanafaTransformative Artificial Intelligence provides a comprehensive overview of the latest trends, challenges, applications, and opportunities in the field of Artificial Intelligence. The book covers the state of the art in AI research, including machine learning, natural language processing, computer vision, and robotics, and explores how these technologies are transforming various industries and domains, such as healthcare, finance, education, and entertainment.The book also addresses the challenges that come with the widespread adoption of AI, including ethical concerns, bias, and the impact on jobs and society. It provides insights into how to mitigate these challenges and how to design AI systems that are responsible, transparent, and trustworthy.The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities.Overall, the book is an essential read for anyone who wants to stay ahead of the curve in the rapidly evolving field of Artificial Intelligence and understand the impact that this transformative technology will have on our lives in the coming years.
Transformative AI: Responsible, Transparent, and Trustworthy AI systems (River Publishers Series in Computing and Information Science and Technology)
by Ahmed BanafaTransformative Artificial Intelligence provides a comprehensive overview of the latest trends, challenges, applications, and opportunities in the field of Artificial Intelligence. The book covers the state of the art in AI research, including machine learning, natural language processing, computer vision, and robotics, and explores how these technologies are transforming various industries and domains, such as healthcare, finance, education, and entertainment.The book also addresses the challenges that come with the widespread adoption of AI, including ethical concerns, bias, and the impact on jobs and society. It provides insights into how to mitigate these challenges and how to design AI systems that are responsible, transparent, and trustworthy.The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities.Overall, the book is an essential read for anyone who wants to stay ahead of the curve in the rapidly evolving field of Artificial Intelligence and understand the impact that this transformative technology will have on our lives in the coming years.
Building China into a Cyber Superpower: Desires, Drivers, and Devices
by Munish SharmaThis book provides a comprehensive look into China’s emerging cyberspace strategy. It highlights the prime drivers of China’s desire to be a cyber superpower and discusses the ways in which China is turning resources into cyber power.The book analyses China’s domestic cyber policy initiatives, strategy documents, censorship measures, and the rationale behind its strong advocacy for sovereignty in cyberspace. It examines China’s position on the prominent issues of cyberspace governance, norms and security in cyberspace, and key diplomatic initiatives. The book also discusses next-generation networks, artificial intelligence, quantum information sciences, and cyber warfare.An important contribution to the study of China’s cyber policy, the book will be of interest to students and researchers of international relations,Chinese digitalisation, security studies, Chinese politics, international security, Chinese foreign policy, and Chinese economy. It will also be useful to the policymakers and corporate professionals engaged with China’s digital sphere.
Building China into a Cyber Superpower: Desires, Drivers, and Devices
by Munish SharmaThis book provides a comprehensive look into China’s emerging cyberspace strategy. It highlights the prime drivers of China’s desire to be a cyber superpower and discusses the ways in which China is turning resources into cyber power.The book analyses China’s domestic cyber policy initiatives, strategy documents, censorship measures, and the rationale behind its strong advocacy for sovereignty in cyberspace. It examines China’s position on the prominent issues of cyberspace governance, norms and security in cyberspace, and key diplomatic initiatives. The book also discusses next-generation networks, artificial intelligence, quantum information sciences, and cyber warfare.An important contribution to the study of China’s cyber policy, the book will be of interest to students and researchers of international relations,Chinese digitalisation, security studies, Chinese politics, international security, Chinese foreign policy, and Chinese economy. It will also be useful to the policymakers and corporate professionals engaged with China’s digital sphere.
Learn R: As a Language (Chapman & Hall/CRC The R Series)
by Pedro J. AphaloLearning a computer language like R can be either frustrating, fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward for overcoming them. The book is designed so that it includes smaller and bigger challenges, in what I call playgrounds, in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. For students and professionals in the biological sciences, humanities and many applied fields, recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide, encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2024 and beyond.What is new in the second edition? Text expanded by more than 25% to include additional R features and gentler and more detailed explanations Contains 24 new diagrams and flowcharts, seven new tables, and revised text and code examples for clarity All three indexes were expanded, and answers to 28 frequently asked questions added What will you find in this book? Programming concepts explained as they apply to current R Emphasis on the role of abstractions in programming Few prescriptive rules—mostly the author’s preferences together with alternatives Presentation of the R language emphasizing the “R way of doing things” Tutoring for “programming in the small” using scripts for data analysis Explanation of the differences between R proper and extensions for data wrangling The grammar of graphics is described as a language for the construction of data visualisations Examples of data exchange between R and the foreign world using common file formats Coaching to become an independent R user, capable of writing original scripts and solving future challenges