Computers

This book lends insight into solving some well-known AI problems using the most efficient problem-solving methods by humans and computers. The book discusses the importance of developing critical-thinking methods and skills, and develops a consistent approach toward each problem. This book assembles in one place a set of interesting and challenging AI–type problems that students regularly encounter in computer science, mathematics, and AI courses. These problems are not new, and students from all backgrounds can benefit from the kind of deductive thinking that goes into solving them. The book is especially useful as a companion to any course in computer science or mathematics where there are interesting problems to solve.

Features:

•Addresses AI and problem-solving from different perspectives
•Covers classic AI problems such as Sudoku, Map Coloring, Twelve Coins, Red Donkey, Cryptarithms, Monte Carlo Methods, Rubik’s Cube, Missionaries/Cannibals, Knight’s Tour, Monty Hall, and more
•Includes a companion disc with source code, solutions, figures, and more
•Offers playability sites where students can exercise the process of developing their solutions
•Describes problem-solving methods that might be applied to a variety of situations

eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at info@merclearning.com.

Surviving a Cyberattack: Securing Social Media and Protecting Your Home is a roadmap to navigating the internet with confidence.

This comprehensive guide addresses the ever-growing challenges users face in the online world. It explores various online risks, from social media scams and data breaches to online fraud. Recognizing these threats is crucial for protecting yourself, your loved ones, and even your small business. This hands-on reference equips you with the knowledge and tools needed to navigate the online landscape safely. It covers essential topics like securing your router and social media accounts, protecting personal information, and mitigating risks for children and vulnerable adults. Additionally, it offers valuable insights on online shopping safety, responsible technology disposal, and surviving a cyberattack.

You’ll learn about

• Safeguarding devices and how to master router configuration,　identifying IoT risks,　and creating impenetrable defenses.
• Navigating social media and securing accounts,　understanding privacy settings,　and banishing social media scams.
• Protecting your children and how to foster responsible online habits,　managing their digital access,　and keeping them safe from harm.
• Securing a small business and shielding data from cyberattacks,　avoiding business scams,　and ensuring responsible social media use.
• Caring for vulnerable family members and protecting them from online predators,　managing their digital accounts,　and handling sensitive topics like digital estate planning.
• Bouncing back from attacks and learning how to properly use data backup practices,　understand reporting procedures,　and emerge stronger from any digital mishap.

This book describes common threats to your cybersecurity and practical steps you can take to avoid them. Threats explained include weak or reused passwords, malware, viruses, social engineering, outdated software, ransomware, the internet of things (IoT) and risky Internet browsing. Tools and techniques to help enhance your security like multi-factor authentication (MFA), firewalls, backups, virtual private networks (VPN) are also explained.

•Discusses how weak passwords can lead to vulnerabilities and how to create strong ones that are easy to remember.
• Describes social engineering attacks, why you may be vulnerable to them and how to protect yourself.
•Explains how Multi-Factor Authentication (MFA) works and how to enable it.
•Presents how to protect your system against a Ransomware attack.

Covering all of the major techniques, this book uses both metric and imperial units to illustrate the myriad drawing and editing tools for this popular application. Use the companion files to set up drawing exercises and projects and to see all of the book’s figures. Revit 2025 Architecture includes over 50 “mini-workshops” that complete small projects from concept through actual plotting. Solving all of these workshops will help to master Revit Architecture from beginning to end, without overlooking any of the basic commands and functions. Companion files available for downloading with projects from the book.

FEATURES

• Uses both metric and imperial units to illustrate the myriad drawing and editing tools
• Includes over 50 “mini-workshops” and hundreds of figures that complete small projects
• Helps you to prepare for the Revit Architecture Certified Professional exam
• Exercises and projects included for use as a textbook
• Companion files available for downloading with projects from the book.

BRIEF TABLE OF CONTENTS:

A Next Big Idea Club "Must Read" for December 2023

As all aspects of our social and informational lives increasingly migrate online, the line between what is "real" and what is digitally fabricated grows ever thinner—and that fake content has undeniable real-world consequences. A History of Fake Things on the Internet takes the long view of how advances in technology brought us to the point where faked texts, images, and video content are nearly indistinguishable from what is authentic or true.

Computer scientist Walter J. Scheirer takes a deep dive into the origins of fake news, conspiracy theories, reports of the paranormal, and other deviations from reality that have become part of mainstream culture, from image manipulation in the nineteenth-century darkroom to the literary stylings of large language models like ChatGPT. Scheirer investigates the origins of Internet fakes, from early hoaxes that traversed the globe via Bulletin Board Systems (BBSs), USENET, and a new messaging technology called email, to today's hyperrealistic, AI-generated Deepfakes. An expert in machine learning and recognition, Scheirer breaks down the technical advances that made new developments in digital deception possible, and shares behind-the-screens details of early Internet-era pranks that have become touchstones of hacker lore. His story introduces us to the visionaries and mischief-makers who first deployed digital fakery and continue to influence how digital manipulation works—and doesn't—today: computer hackers, digital artists, media forensics specialists, and AI researchers. Ultimately, Scheirer argues that problems associated with fake content are not intrinsic properties of the content itself, but rather stem from human behavior, demonstrating our capacity for both creativity and destruction.

Explore the transformative world of AI-driven marketing by integrating Artificial Intelligence into modern marketing strategies. This book is designed to help businesses optimize their operations, personalize customer experiences, and harness the full potential of AI to drive growth and innovation. You will learn the foundational concepts of AI and machine learning, discover best practices for data hygiene, structuring, and optimization, and explore how AI tools can transform customer data into actionable insights, enhancing your ability to create personalized and effective marketing campaigns. The book is tailored for marketing professionals, business owners, and digital strategists who are eager to integrate AI into their marketing practices. It is equally valuable for beginners and experienced marketers who want to stay at the forefront of the rapidly evolving digital marketing landscape.

FEATURES

• Includes step-by-step guides for implementing AI tools in SEO, social media, and email
• Covers the use of AI to analyze customer behavior, benefits of chatbots, and AI-powered customer service
• Features real-world cases from leading companies like Netflix, Amazon, and Spotify
• Uses AI tools to transform customer data into actionable insights for more effective campaigns

TABLE OF CONTENTS

This book is a guide to navigating the evolving landscape of artificial intelligence. Designed for both novices and seasoned professionals it covers a broad range of topics from fundamental ideas to innovative advancements. Readers will investigate the principles of machine learning, explore the intricacies of deep learning architectures, and discover the applications of natural language processing and computer vision. With its concise explanations and useful examples, it gives readers the knowledge and abilities they need to confidently traverse the changing field of artificial intelligence. This text also looks at real-world case studies and important ethical issues, providing insightful information about the ethical ramifications and societal effects of technology.

Features:

• Practical applications and case studies with a section on use cases across various industries, including healthcare, finance, transportation, and retail.
• Actionable steps for getting started with AI include how to set up an AI development environment, learning Python for AI applications, and utilizing popular AI libraries.
• Resources for further study including, AI online courses, AI communities and forums, and recommended books essentially, a roadmap for continuous learning.

Discrete Mathematics presents the material in an easily accessible manner. Beside the usual content (expanded a little bit), a special writing style is used.

We start with the natural numbers, function and relations, as well as the powerset lattice. The second chapter illustrates set theory with its laws and the Generalized Continuum Hypothesis. Chapter 3 delivers Boolean Algebra, with the double exponential formula for the # different boolean functions. The next chapter covers the induction, direct, and indirect proof. Chapter 5 presents combinatorics: Rules of sum, product, quotient, the pigeonhole principle, in/exclusion, permutation and binomial coefficient, plus Stirling numbers of 1^st and 2^nd kind as well as the Bell number; additionally, the recurrence relation with back- and forward reasoning is offered. We conclude with general and conditional probability, incl. the Monty Hall problem.

Discrete Mathematics presents the material in a lively fashion, including topics which are usually not presented. Providing an annex with questions and solutions it offers the chance to the readers worldwide to grasp the subject in this handy and clearly arranged treatise.

The book provides best practices from online educators who are engaged in online teaching and program development in Christian higher education. It also explores the distinct aspects of teaching and developing online courses and programs from a Christian perspective and within Christian higher education institutions. As such it is can serve as a ready resource for academic administrators and professors, novices and veterans at online program development and instruction.

Podcast Studies: Practice into Theory critically examines the emergent field of podcasting in academia, revealing its significant impact on scholarly communication and approaches to research and knowledge creation.

This collection presents in-depth analyses from scholars who have integrated podcasting into their academic pursuits. The book systematically explores the medium's implications for teaching, its effectiveness in reaching broader audiences, and its role in reshaping the dissemination of academic work. Covering a spectrum of disciplines, the contributors detail their engagement with podcasting, providing insight into its use as both a research tool and an object of analysis, thereby illuminating the multifaceted ways in which podcasting intersects with and influences academic life.

The volume provides substantive evidence of podcasting's transformative effect on academia, offering reflections on its potential to facilitate a more accessible and engaging form of scholarly output. By presenting case studies and empirical research, Podcast Studies: Practice into Theory underscores the originality of podcasting as an academic endeavor and its utility in expanding the reach and impact of scholarly work. It serves as a key resource for academics, researchers, and practitioners interested in the application and study of podcasting as a novel vector for knowledge creation and distribution.

There are many myths about Artificial Intelligence (AI) relating to what it is and what it can and cannot do. The people making decisions on AI projects are often not technologically savvy and unable to find easy answers. The spending on and the returns from AI projects are not necessarily straightforward. Part of the reason for this is the lack of understanding of the impact of critical decision criteria. AI touches on many ethical concepts - data privacy, validity, and, more importantly, its potential misuse. AI often replaces human decision-making, as managers do not clearly understand the implications of those choices. This book provides an easy and accessible guide for practitioners without a technological background to understand AI. It guides the reader through the fundamental issues confronting decision-makers. It offers advice on ‘how to ask relevant questions’ using the 15 decision scales. There is currently no comparable book on the market that acts as a pocketbook management reference guide for the AI layman.

The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased.

Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing.

In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.

Crossing the Bridge of the Digital Divide: A Walk with Global Leaders explores the combined effect of the rapid growth of information as an increasingly fragmented information base, a large component of which is available only to people with money and/or acceptable institutional affiliations. In the recent past, the outcome of these challenges has been characterized as the 'digital divide' between the information 'haves' and 'have nots' along racial and socio economic lines that seem to widen as time passes. To address the issues of digital equity and digital inequality in an effort to bridge the digital divide, educational scholars, researchers and practitioners are in positions to ensure equitable opportunities are made available for people of all ages, races, ability, sexual orientation, and ethnicity in support of social justice for bridging the digital divide. The digital divide addresses issues concerning equal opportunity, equity and access that have an effect on the development of marginalized and otherwise disenfranchised populations within and across systems nationally and internationally.

The contributing authors- representing Unites States, Canada, South Africa, New Zealand, and the UK - posit that education institutions can serve as the bridge to close the digital divide for students who do not have access to information technology in their homes. At a time when more computers are made available in schools than ever before, the digital divide continues to widen and fewer people in the lowest SES groups are given the opportunity to join the world of computer technology and the internet. As a result, the influence of leadership activity on institutional racism, gender discrimination, inequality of opportunity, inequity of educational processes, digital exclusion, and justice have gained currency and attention.

The contributing national and international authors examine the digital divide in terms of social justice leadership, equity and access. It is within this context that the authors offer discussions from a lens of their choice, i.e. conceptual, review of literature, epistemological, etc. By adopting an educational approach to bridging the digital divide, researchers and practitioners can connect and extend long established lines of conceptual and empirical inquiry aimed at improving organizational practices and thereby gain insights that might be otherwise overlooked, or assumed. This holds great promise for generating, refining, and testing theories of leadership for equity and access, and helps strengthen already vibrant lines of inquiry on social justice.

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner.

Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted form this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups.

Data mining applications are seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner.

Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups.

Data mining applications are in finance (banking, brokerage, and insurance), marketing (customer relationships, retailing, logistics, and travel), as well as in manufacturing, health care, fraud detection, homeland security, and law enforcement.

Feeling guilty about not networking enough? Stop! You can learn how to network effectively without attending networking events, collecting business cards, or getting a lot of LinkedIn followers. How? By learning how to Connect the Dots.

Written by Inga Carboni, Ph.D., Connect the Dots is a fun, fast-paced, and fact-based book for working professionals seeking to take the next step in their careers. The truth is that networking is not about managing impressions or projecting your personal brand. Effective networkers build, nurture, and leverage relationships, real relationships built on genuine connection. When done correctly, networking isn’t sleazy or manipulative. Instead, it’s empowering, for you, for all the people you know, and for all the people they know.

Connect the Dots: How to Build, Nurture, and Leverage Your Network to Achieve Your Personal and Professional Goals offers a combination of personal stories, business anecdotes, self-assessments, exercises, and concrete guidelines grounded in the latest scientific research. Connect the Dots focuses on developing your personal power and leadership skills by creating effective networks and networking effectively. This book is designed to benefit everyone, from young professionals to senior managers to human resource professionals to C-suite executives.

Unleash the power of your network by learning how to connect the dots to make your network work for you.

Virtual Worlds are being increasingly used in business and education. With each day more people are venturing into computer generated online persistent worlds such as Second Life for increasingly diverse reasons such as commerce, education, research, and entertainment. This book explores the emerging ethical issues associated with these novel environments for human interaction and cutting-edge approaches to these new ethical problems. This volume’s goal is to put forward a number of these virtual world ethical issues of which research is only commencing. The developing literature specifically regarding virtual world ethics is a recent phenomenon. Research based on the phenomenon of virtual world life has only been developing in the past four years. This volume introduces pathbreaking work in a field which is only just beginning to take shape. It is ideal as both as a library reference and a supplementary text in upper-division courses focused on the issues of applied ethics and new media. It is unique in being one of the first volumes specifically addressed to ethical problems of the “metaverse”.

This volume includes articles from authors from around the world exploring topics such as: employing rationalist and casuistic approaches to the controversial topic of “virtual rape” yield an increased understanding of how virtual worlds ought to be designed, the relationship between the ethical and legal dimensions of virtual world users’ participation in “paratexts”, utilitarian consideration of harm and freedom in the case of virtual pedophilia, norms of research ethics in virtual worlds, the ethical implications of employing virtual worlds as tools for medical education and experimenting with healthcare services, the ethics of the collective action of virtual world communities, consideration of the virtue and potential of cosmopolitanism in virtual worlds, Deleuzian ethical approaches to the experience of the disabled in virtual worlds, the ethics of virtual world design, and the ethical implications of the “illusion of reality” presented by virtual worlds.

The Association officially endorses this definition of Instructional Technology which has been developed over three years by the Committee on Definition and Terminology. The Association recognizes that other theoretical frameworks exist and that these are valid, but believes that these are part of the more inclusive theoretical framework of Instructional Technology used in this definition. In making this definition and the document explaining it available, we hope to help other organizations clarify their relationship to the broad field of Instructional Technology. Although the Association offers this definition as its current position, it is committed to a continuous reevaluation of the definition and to revising and publishing it so that it reflects changing concepts and terminology.

A document of this magnitude can only be produced as the result of the dedication and effort of the persons who formed the committee and of its chairperson, Barbara Seels and her collaborator, Rita C. Richey. Without their energies, skill, perseverance, and willingness to risk stating their perceptions in this format we could not have offered this document. Whether or not we agree with the statements presented here, they will provide a benchmark and a point of dialogue for further development of a profession which seeks to provide conditions for effective learning.

The general theme of this book is to present innovative psychometric modeling and methods. In particular, this book includes research and successful examples of modeling techniques for new data sources from digital assessments, such as eye-tracking data, hint uses, and process data from game-based assessments. In addition, innovative psychometric modeling approaches, such as graphical models, item tree models, network analysis, and cognitive diagnostic models, are included.

Chapters 1, 2, 4 and 6 are about psychometric models and methods for learning analytics. The first two chapters focus on advanced cognitive diagnostic models for tracking learning and the improvement of attribute classification accuracy. Chapter 4 demonstrates the use of network analysis for learning analytics. Chapter 6 introduces the conjunctive root causes model for the understanding of prerequisite skills in learning. Chapters 3, 5, 8, 9 are about innovative psychometric techniques to model process data. Specifically, Chapters 3 and 5 illustrate the usage of generalized linear mixed effect models and item tree models to analyze eye-tracking data. Chapter 8 discusses the modeling approach of hint uses and response accuracy in learning environment. Chapter 9 demonstrates the identification of observable outcomes in the game-based assessments. Chapters 7 and 10 introduce innovative latent variable modeling approaches, including the graphical and generalized linear model approach and the dynamic modeling approach.

In summary, the book includes theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to model and analyze multiple data sources from digital assessments. When computer-based assessments are emerging and evolving, it is important that researchers can expand and improve the methods for modeling and analyzing new data sources. This book provides a useful resource to researchers who are interested in the development of psychometric methods to solve issues in this digital assessment age.

As sensors spread across almost every industry, the internet of things is going to trigger a massive influx of big data. We delve into where IoT will have the biggest impact and what it means for the future of big data analytics. Internet of Things is changing the face of different sectors such as manufacturing, health-care, business, education etc. by completely redefining the way people, devices, and apps connect and interact with each other in the eco system. From personal fitness and wellness sensors, implantable devices to surgical robots – IoT is bringing in new tools and efficiencies in the ecosystem resulting in more integrated healthcare. Application of computational intelligence techniques is today considered as a key success factor to solve the growing scale and complexity of problems in the field of health care systems, agriculture, e-commerce etc.

The convergence of Computational intelligence, Big Data and IoT provides new opportunities and revolutionize business in huge way. This book will support industry and governmental agencies to facilitate and make sense of myriad connected devices in coming decade. This book offers the recent advancements in Computational Intelligence, IoT and Big Data Analytics.

• Development of models and algorithms for employing IoT based facilities in healthcare, industry, agriculture, e- commerce, manufacturing, business etc.
• Methods for collection, management retrieval and processing of Big Data in various domains.
• Provides taxonomy of challenges, issues and research directions in applications of computational intelligence techniques in different domains

With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better understand the assessment products or accuracy and the process how an item product was attained. The analysis of the conventional and non-conventional assessment data calls for more methodology other than the latent trait modeling.

Natural language processing (NLP) methods and machine learning algorithms have been successfully applied in automated scoring. It has been explored in providing diagnostic feedback to test-takers in writing assessment. Recently, machine learning algorithms have been explored for cheating detection and cognitive diagnosis. When the measurement field promote the use of assessment data to provide feedback to improve teaching and learning, it is the right time to explore new methodology and explore the value added from other data sources. This book presents the use cases of machine learning and NLP in improving the assessment theory and practices in high-stakes summative assessment, learning, and instruction. More specifically, experts from the field addressed the topics related to automated item generations, automated scoring, automated feedback in writing, explainability of automated scoring, equating, cheating and alarming response detection, adaptive testing, and applications in science assessment. This book demonstrates the utility of machine learning and NLP in assessment design and psychometric analysis.

Computer science is increasingly becoming an essential 21st century skill. As school systems around the world recognize the importance of computer science, demand for teachers who have the knowledge and skills to deliver computer science instruction is rapidly growing. Yet a number of recent studies indicate that teachers report low confidence and limited understanding of computer science, frequently confusing basic computer literacy skills with computer science. This is true for both teachers at the K-8 level as well as secondary education teachers who frequently transition to computer science from other content areas, such as mathematics. As computer science is not yet included in most teacher preparation programs, professional development is a critical step in efforts to prepare in-service teachers to deliver high-quality computer science instruction. To date, however, research on best practices in computer science professional development has been severely lacking in the literature, making it difficult for researchers and practitioners alike to examine effective in-service preparation models.

This book provide examples of professional development approaches that help teachers integrate aspects of computing in existing curricula at the K-8 level or deliver stand-alone computer science courses at the secondary school level. Further, this book identifies computational competencies for teachers, promising pedagogical strategies that advance teacher learning, as well as alternative pathways for ongoing learning including microcredentials. The primary audience of the book is graduate students and faculty in educational technology, educational or cognitive psychology, learning theory, curriculum and instruction, computer science, instructional systems and learning sciences. Additionally, the book will serve as a valuable addition to education practitioners and curriculum developers as well as policy makers looking to increase the number of teachers who are prepared to deliver computing education.

This book will provide a comprehensive overview of business analytics, for those who have either a technical background (quantitative methods) or a practitioner business background. Business analytics, in the context of the 4th Industrial Revolution, is the “new normal” for businesses that operate in this digital age. This book provides a comprehensive primer and overview of the field (and related fields such as Business Intelligence and Data Science). It will discuss the field as it applies to financial institutions, with some minor departures to other industries. Readers will gain understanding and insight into the field of data science, including traditional as well as emerging techniques. Further, many chapters are dedicated to the establishment of a data-driven team – from executive buy-in and corporate governance to managing and quantifying the return of data-driven projects.

Computer science has emerged as a key driver of innovation in the 21st century. Yet preparing teachers to teach computer science or integrate computer science content into K-12 curricula remains an enormous challenge. Recent policy reports have suggested the need to prepare future teachers to teach computer science through pre-service teacher education programs. In order to prepare a generation of teachers who are capable of delivering computer science to students, however, the field must identify research-based examples, pedagogical strategies, and policies that can facilitate changes in teacher knowledge and practices.

The purpose of this book is to provide examples that could help guide the design and delivery of effective teacher preparation on the teaching of computer science.

This book identifies promising pathways, pedagogical strategies, and policies that will help teacher education faculty and pre-service teachers infuse computer science content into their curricula as well as teach stand-alone computing courses. Specifically, the book focuses on pedagogical practices for developing and assessing pre-service teacher knowledge of computer science, course design models for pre-service teachers, and discussion of policies that can support the teaching of computer science. The primary audience of the book is students and faculty in educational technology, educational or cognitive psychology, learning theory, teacher education, curriculum and instruction, computer science, instructional systems, and learning sciences.

Unlock data-driven decision-making with Business Intelligence and Data Analysis in the Age of AI. This guide combines traditional BI with AI’s transformative power to help professionals and newcomers excel in the data era. Whether you're a seasoned professional or new to BI, this book provides actionable strategies to navigate the complexities of modern data analysis. Embark on this illuminating journey to master the tools, strategies, and ethical considerations that define modern business intelligence and AI.
FEATURES

• BI Fundamentals: Master analytics processes and tools
• Ethical and Regulatory Challenges: Navigate governance, security, privacy, and ethical frameworks
• BI Tools: Learn the power of tools like R, SQL, Python, and data manipulation techniques
• Visualize and Predict: Learn data visualization and predictive analytics to forecast trends and drive innovation
• Embrace the Future: Discover how AI transforms BI, unlocking new opportunities and navigating emerging risks.