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| data science job outlook 2025: Designing Great Data Products Jeremy Howard, Margit Zwemer, Mike Loukides, 2012-03-23 In the past few years, we’ve seen many data products based on predictive modeling. These products range from weather forecasting to recommendation engines like Amazon's. Prediction technology can be interesting and mathematically elegant, but we need to take the next step: going from recommendations to products that can produce optimal strategies for meeting concrete business objectives. We already know how to build these products: they've been in use for the past decade or so, but they're not as common as they should be. This report shows how to take the next step: to go from simple predictions and recommendations to a new generation of data products with the potential to revolutionize entire industries. |
| data science job outlook 2025: Evil Robots, Killer Computers, and Other Myths Steven Shwartz, 2021-02-09 Are AI robots and computers really going to take over the world? Longtime artificial intelligence (AI) researcher and investor Steve Shwartz has grown frustrated with the fear-inducing hype around AI in popular culture and media. Yes, today’s AI systems are miracles of modern engineering, but no, humans do not have to fear robots seizing control or taking over all our jobs. In this exploration of the fascinating and ever-changing landscape of artificial intelligence, Dr. Shwartz explains how AI works in simple terms. After reading this captivating book, you will understand • the inner workings of today’s amazing AI technologies, including facial recognition, self-driving cars, machine translation, chatbots, deepfakes, and many others; • why today’s artificial intelligence technology cannot evolve into the AI of science fiction lore; • the crucial areas where we will need to adopt new laws and policies in order to counter threats to our safety and personal freedoms resulting from the use of AI. So although we don’t have to worry about evil robots rising to power and turning us into pets—and we probably never will—artificial intelligence is here to stay, and we must learn to separate fact from fiction and embrace how this amazing technology enhances our world. |
| data science job outlook 2025: How to Lead in Data Science Jike Chong, Yue Cathy Chang, 2021-12-28 A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples. In How To Lead in Data Science you will learn: Best practices for leading projects while balancing complex trade-offs Specifying, prioritizing, and planning projects from vague requirements Navigating structural challenges in your organization Working through project failures with positivity and tenacity Growing your team with coaching, mentoring, and advising Crafting technology roadmaps and championing successful projects Driving diversity, inclusion, and belonging within teams Architecting a long-term business strategy and data roadmap as an executive Delivering a data-driven culture and structuring productive data science organizations How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas. About the technology Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. About the book How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself. What's inside How to coach and mentor team members Navigate an organization’s structural challenges Secure commitments from other teams and partners Stay current with the technology landscape Advance your career About the reader For data science practitioners at all levels. About the author Dr. Jike Chong and Yue Cathy Chang build, lead, and grow high-performing data teams across industries in public and private companies, such as Acorns, LinkedIn, large asset-management firms, and Fortune 50 companies. Table of Contents 1 What makes a successful data scientist? PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP 2 Capabilities for leading projects 3 Virtues for leading projects PART 2 THE MANAGER: NURTURING A TEAM 4 Capabilities for leading people 5 Virtues for leading people PART 3 THE DIRECTOR: GOVERNING A FUNCTION 6 Capabilities for leading a function 7 Virtues for leading a function PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY 8 Capabilities for leading a company 9 Virtues for leading a company PART 5 THE LOOP AND THE FUTURE 10 Landscape, organization, opportunity, and practice 11 Leading in data science and a future outlook |
| data science job outlook 2025: Content Inc.: How Entrepreneurs Use Content to Build Massive Audiences and Create Radically Successful Businesses Joe Pulizzi, 2015-09-04 “Instead of throwing money away and sucking up to A-listers, now there is a better way to promote your business. It’s called content marketing, and this book is a great way to master this new technique.” -Guy Kawasaki, Chief evangelist of Canva and author of The Art of the Start 2.0 How do you take the maximum amount of risk out of starting a business? Joe Pulizzi shows us. Fascinate your audience, then turn them into loyal fans. Content Inc. shows you how. Use it as your roadmap to startup success.” -Sally Hogshead, New York Times and Wall Street Journal bestselling author, How the World Sees You If you're serious about turning content into a business, this is the most detailed, honest, and useful book ever written. -Jay Baer, New York Times bestselling author of Youtility The approach to business taught all over the world is to create a product and then spend a bunch of money to market and sell it. Joe outlines a radically new way to succeed in business: Develop your audience first by creating content that draws people in and then watch your business sell themselves! -David Meerman Scott bestselling author of ten books including The New Rules of Sales and Service The digital age has fundamentally reshaped the cost curve for entrepreneurs. Joe describes the formula for developing a purpose-driven business that connects with an engaged and loyal audience around content. With brand, voice and audience, building and monetizing a business is easy. -Julie Fleischer, Sr. Director, Data + Content + Media, Kraft Foods What if you launched a business with nothing to sell, and instead focused first on serving the needs of an audience, trusting that the 'selling' part would come later? Crazy? Or crazy-brilliant? I'd say the latter. Because in today's world, you should serve before selling. -Ann Handley, author of the Wall Street Journal bestseller Everybody Writes and Content Rules Today, anyone, anywhere with a passion and a focus on a content niche can build a multi-million dollar platform and business. I did it and so can you. Just follow Joe's plan and hisContent Inc. model. -John Lee Dumas, Founder, EntrepreneurOnFire The Internet doesn't need more content. It needs amazing content. Content Inc is the business blueprint on how to achieve that. If you're in business and are tired of hearing about the need for content marketing, but want the how and the proof, Content Inc is your blueprint. -Scott Stratten, bestselling author and President of UnMarketing Inc. Content marketing is by far the best marketing strategy for every company and Joe is by far the best guru on the topic. I wish this book was available when we started our content marketing initiative. It would have saved us a huge amount of time and effort! -Scott Maxwell, Managing Partner/Founder OpenView Venture Partners |
| data science job outlook 2025: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| data science job outlook 2025: Career Guide to Industries , 2006 |
| data science job outlook 2025: Think Like a Data Scientist Brian Godsey, 2017-03-09 Summary Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scientist. This book will get you there. About the Book Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. As you read, you'll discover (or remember) valuable statistical techniques and explore powerful data science software. More importantly, you'll put this knowledge together using a structured process for data science. When you've finished, you'll have a strong foundation for a lifetime of data science learning and practice. What's Inside The data science process, step-by-step How to anticipate problems Dealing with uncertainty Best practices in software and scientific thinking About the Reader Readers need beginner programming skills and knowledge of basic statistics. About the Author Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups. Table of Contents PART 1 - PREPARING AND GATHERING DATA AND KNOWLEDGE Philosophies of data science Setting goals by asking good questions Data all around us: the virtual wilderness Data wrangling: from capture to domestication Data assessment: poking and prodding PART 2 - BUILDING A PRODUCT WITH SOFTWARE AND STATISTICS Developing a plan Statistics and modeling: concepts and foundations Software: statistics in action Supplementary software: bigger, faster, more efficient Plan execution: putting it all together PART 3 - FINISHING OFF THE PRODUCT AND WRAPPING UP Delivering a product After product delivery: problems and revisions Wrapping up: putting the project away |
| data science job outlook 2025: It's All Analytics! Scott Burk, Gary D. Miner, 2020-05-25 It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, analytics, is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series. |
| data science job outlook 2025: Careers in Information Science Louise Schultz, 1963 Presents copy for use as a reference brochure and a giveaway sheet to be distributed to guidance counselors to help them direct young people into the growing field of Information Science. Sets forth that Information Science is concerned with the properties, behavior, and flow of information. Describes how it is used, both by individuals and in large systems. Discusses the opportunities in Information Science and outlines three relatively different career areas: (1) Special Librarianship; (2) Literature Analysis; and (3) Information System Design. Details an educational program appropriate for participation in these career areas. Concludes that Information Science is a new but rapidly growing field pushing the frontiers of human knowledge and, thus, contributing to human well-being and progress. (Author). |
| data science job outlook 2025: Global Trends 2025: A Transformed World Office of the Director of National Intelligence (U.S.), 2013-08-15 Global Trends 2025: A Transformed World is the fourth unclassified report prepared by the National Intelligence Council (NIC) in recent years that takes a long-term view of the future. It offers a fresh look at how key global trends might develop over the next 15 years to influence world events. Our report is not meant to be an exercise in prediction or crystal ball-gazing. Mindful that there are many possible futures, we offer a range of possibilities and potential discontinuities, as a way of opening our minds to developments we might otherwise miss. (From the NIC website) |
| data science job outlook 2025: Process Mining Wil M. P. van der Aalst, 2016-04-15 This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers. |
| data science job outlook 2025: Ask a Manager Alison Green, 2018-05-01 From the creator of the popular website Ask a Manager and New York’s work-advice columnist comes a witty, practical guide to 200 difficult professional conversations—featuring all-new advice! There’s a reason Alison Green has been called “the Dear Abby of the work world.” Ten years as a workplace-advice columnist have taught her that people avoid awkward conversations in the office because they simply don’t know what to say. Thankfully, Green does—and in this incredibly helpful book, she tackles the tough discussions you may need to have during your career. You’ll learn what to say when • coworkers push their work on you—then take credit for it • you accidentally trash-talk someone in an email then hit “reply all” • you’re being micromanaged—or not being managed at all • you catch a colleague in a lie • your boss seems unhappy with your work • your cubemate’s loud speakerphone is making you homicidal • you got drunk at the holiday party Praise for Ask a Manager “A must-read for anyone who works . . . [Alison Green’s] advice boils down to the idea that you should be professional (even when others are not) and that communicating in a straightforward manner with candor and kindness will get you far, no matter where you work.”—Booklist (starred review) “The author’s friendly, warm, no-nonsense writing is a pleasure to read, and her advice can be widely applied to relationships in all areas of readers’ lives. Ideal for anyone new to the job market or new to management, or anyone hoping to improve their work experience.”—Library Journal (starred review) “I am a huge fan of Alison Green’s Ask a Manager column. This book is even better. It teaches us how to deal with many of the most vexing big and little problems in our workplaces—and to do so with grace, confidence, and a sense of humor.”—Robert Sutton, Stanford professor and author of The No Asshole Rule and The Asshole Survival Guide “Ask a Manager is the ultimate playbook for navigating the traditional workforce in a diplomatic but firm way.”—Erin Lowry, author of Broke Millennial: Stop Scraping By and Get Your Financial Life Together |
| data science job outlook 2025: Programming Machine Learning Paolo Perrotta, 2020-03-31 You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It's easy to be intimidated, even as a software developer. The good news is that it doesn't have to be that hard. Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system. Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty. Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning. Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work. Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on. Iterate on your design, and add layers of complexity as you go. Build an image recognition application from scratch with supervised learning. Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning. Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets. Train and refine those networks with backpropagation and batching. Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system. Start from the beginning and code your way to machine learning mastery. What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly. Apart from that, you'll only need your computer, and your code-adept brain. |
| data science job outlook 2025: The Future of the Nursing Workforce in the United States Peter Buerhaus, Douglas Staiger, David Auerbach, 2009-10-06 The Future of the Nursing Workforce in the United States: Data, Trends and Implications provides a timely, comprehensive, and integrated body of data supported by rich discussion of the forces shaping the nursing workforce in the US. Using plain, jargon free language, the book identifies and describes the key changes in the current nursing workforce and provide insights about what is likely to develop in the future. The Future of the Nursing Workforce offers an in-depth discussion of specific policy options to help employers, educators, and policymakers design and implement actions aimed at strengthening the current and future RN workforce. The only book of its kind, this renowned author team presents extensive data, exhibits and tables on the nurse labor market, how the composition of the workforce is evolving, changes occurring in the work environment where nurses practice their profession, and on the publics opinion of the nursing profession. |
| data science job outlook 2025: Alternative Careers in Science Cynthia Robbins-Roth, 1998 You can do more with your science degree than you ever dreamed. In this book, readers will meet scientists who evolved into Wall Street analysts, science policy gurus, patent agents, journalists, and top-flight sales reps. Each chapter covers a different career track and shows why having a graduate degree in science gives you an edge. |
| data science job outlook 2025: Neuromorphic Photonics Paul R. Prucnal, Bhavin J. Shastri, 2017-05-08 This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of neuromorphic photonics. It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field. |
| data science job outlook 2025: Embedded System Design Peter Marwedel, 2010-11-16 Until the late 1980s, information processing was associated with large mainframe computers and huge tape drives. During the 1990s, this trend shifted toward information processing with personal computers, or PCs. The trend toward miniaturization continues and in the future the majority of information processing systems will be small mobile computers, many of which will be embedded into larger products and interfaced to the physical environment. Hence, these kinds of systems are called embedded systems. Embedded systems together with their physical environment are called cyber-physical systems. Examples include systems such as transportation and fabrication equipment. It is expected that the total market volume of embedded systems will be significantly larger than that of traditional information processing systems such as PCs and mainframes. Embedded systems share a number of common characteristics. For example, they must be dependable, efficient, meet real-time constraints and require customized user interfaces (instead of generic keyboard and mouse interfaces). Therefore, it makes sense to consider common principles of embedded system design. Embedded System Design starts with an introduction into the area and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, like real-time operating systems. The book also discusses evaluation and validation techniques for embedded systems. Furthermore, the book presents an overview of techniques for mapping applications to execution platforms. Due to the importance of resource efficiency, the book also contains a selected set of optimization techniques for embedded systems, including special compilation techniques. The book closes with a brief survey on testing. Embedded System Design can be used as a text book for courses on embedded systems and as a source which provides pointers to relevant material in the area for PhD students and teachers. It assumes a basic knowledge of information processing hardware and software. Courseware related to this book is available at http://ls12-www.cs.tu-dortmund.de/~marwedel. |
| data science job outlook 2025: The Ethical Algorithm Michael Kearns, Aaron Roth, 2020 Algorithms have made our lives more efficient and entertaining--but not without a significant cost. Can we design a better future, one in which societial gains brought about by technology are balanced with the rights of citizens? The Ethical Algorithm offers a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. |
| data science job outlook 2025: Global Trends 2040 National Intelligence Council, 2021-03 The ongoing COVID-19 pandemic marks the most significant, singular global disruption since World War II, with health, economic, political, and security implications that will ripple for years to come. -Global Trends 2040 (2021) Global Trends 2040-A More Contested World (2021), released by the US National Intelligence Council, is the latest report in its series of reports starting in 1997 about megatrends and the world's future. This report, strongly influenced by the COVID-19 pandemic, paints a bleak picture of the future and describes a contested, fragmented and turbulent world. It specifically discusses the four main trends that will shape tomorrow's world: - Demographics-by 2040, 1.4 billion people will be added mostly in Africa and South Asia. - Economics-increased government debt and concentrated economic power will escalate problems for the poor and middleclass. - Climate-a hotter world will increase water, food, and health insecurity. - Technology-the emergence of new technologies could both solve and cause problems for human life. Students of trends, policymakers, entrepreneurs, academics, journalists and anyone eager for a glimpse into the next decades, will find this report, with colored graphs, essential reading. |
| data science job outlook 2025: Imagining the Internet Janna Quitney Anderson, 2005-07-21 In the early 1990s, people predicted the death of privacy, an end to the current concept of 'property,' a paperless society, 500 channels of high-definition interactive television, world peace, and the extinction of the human race after a takeover engineered by intelligent machines. Imagining the Internet zeroes in on predictions about the Internet's future and revisits past predictions—and how they turned out. It gives the history of communications in a nutshell, illustrating the serious impact of pervasive networks and how they will change our lives over the next century. |
| data science job outlook 2025: Advanced Selenium Web Accessibility Testing Narayanan Palani, 2019-03-27 This book explains the steps necessary to write manual accessibility tests and convert them into automated selenium-based accessibility tests to run part of regression test packs. If you are searching a topic on Google or buying a product online, web accessibility is a basic need. If a web page is easier to access when using a mouse and complex to navigate with keyboard, this is extremely difficult for users with disabilities. Web Accessibility Testing is a most important testing practice for customers facing web applications. This book explains the steps necessary to write manual accessibility tests and convert them into automated selenium-based accessibility tests to run part of regression test packs. WCAG and Section 508 guidelines are considered across the book while explaining the test design steps. Software testers with accessibility testing knowledge are in high demand at large organizations since the need to do manual and automated accessibility testing is growing rapidly. This book illustrates the types of accessibility testing with test cases and code examples. |
| data science job outlook 2025: The Job Ellen Ruppel Shell, 2018-10-23 Critically acclaimed journalist Ellen Ruppel Shell uncovers the true cost--political, economic, social, and personal--of America's mounting anxiety over jobs, and what we can do to regain control over our working lives. Since 1973, our productivity has grown almost six times faster than our wages. Most of us rank so far below the top earners in the country that the winners might as well inhabit another planet. But work is about much more than earning a living. Work gives us our identity, and a sense of purpose and place in this world. And yet, work as we know it is under siege. Through exhaustive reporting and keen analysis, The Job reveals the startling truths and unveils the pervasive myths that have colored our thinking on one of the most urgent issues of our day: how to build good work in a globalized and digitalized world where middle class jobs seem to be slipping away. Traveling from deep in Appalachia to the heart of the Midwestern rust belt, from a struggling custom clothing maker in Massachusetts to a thriving co-working center in Minnesota, she marshals evidence from a wide range of disciplines to show how our educational system, our politics, and our very sense of self have been held captive to and distorted by outdated notions of what it means to get and keep a good job. We read stories of sausage makers, firefighters, zookeepers, hospital cleaners; we hear from economists, computer scientists, psychologists, and historians. The book's four sections take us from the challenges we face in scoring a good job today to work's infinite possibilities in the future. Work, in all its richness, complexity, rewards and pain, is essential for people to flourish. Ellen Ruppel Shell paints a compelling portrait of where we stand today, and points to a promising and hopeful way forward. |
| data science job outlook 2025: The Python Apprentice Robert Smallshire, Austin Bingham, 2017-06-21 Learn the Python skills and culture you need to become a productive member of any Python project. About This Book Taking a practical approach to studying Python A clear appreciation of the sequence-oriented parts of Python Emphasis on the way in which Python code is structured Learn how to produce bug-free code by using testing tools Who This Book Is For The Python Apprentice is for anyone who wants to start building, creating and contributing towards a Python project. No previous knowledge of Python is required, although at least some familiarity with programming in another language is helpful. What You Will Learn Learn the language of Python itself Get a start on the Python standard library Learn how to integrate 3rd party libraries Develop libraries on your own Become familiar with the basics of Python testing In Detail Experienced programmers want to know how to enhance their craft and we want to help them start as apprentices with Python. We know that before mastering Python you need to learn the culture and the tools to become a productive member of any Python project. Our goal with this book is to give you a practical and thorough introduction to Python programming, providing you with the insight and technical craftsmanship you need to be a productive member of any Python project. Python is a big language, and it's not our intention with this book to cover everything there is to know. We just want to make sure that you, as the developer, know the tools, basic idioms and of course the ins and outs of the language, the standard library and other modules to be able to jump into most projects. Style and approach We introduce topics gently and then revisit them on multiple occasions to add the depth required to support your progression as a Python developer. We've worked hard to structure the syllabus to avoid forward references. On only a few occasions do we require you to accept techniques on trust, before explaining them later; where we do, it's to deliberately establish good habits. |
| data science job outlook 2025: World Development Report 2019 World Bank, 2018-10-31 Work is constantly reshaped by technological progress. New ways of production are adopted, markets expand, and societies evolve. But some changes provoke more attention than others, in part due to the vast uncertainty involved in making predictions about the future. The 2019 World Development Report will study how the nature of work is changing as a result of advances in technology today. Technological progress disrupts existing systems. A new social contract is needed to smooth the transition and guard against rising inequality. Significant investments in human capital throughout a person’s lifecycle are vital to this effort. If workers are to stay competitive against machines they need to train or retool existing skills. A social protection system that includes a minimum basic level of protection for workers and citizens can complement new forms of employment. Improved private sector policies to encourage startup activity and competition can help countries compete in the digital age. Governments also need to ensure that firms pay their fair share of taxes, in part to fund this new social contract. The 2019 World Development Report presents an analysis of these issues based upon the available evidence. |
| data science job outlook 2025: Business Statistics for Contemporary Decision Making Ignacio Castillo, Ken Black, Tiffany Bayley, 2023-05-08 Show students why business statistics is an increasingly important business skill through a student-friendly pedagogy. In this fourth Canadian edition of Business Statistics For Contemporary Decision Making authors Ken Black, Tiffany Bayley, and Ignacio Castillo uses current real-world data to equip students with the business analytics techniques and quantitative decision-making skills required to make smart decisions in today's workplace. |
| data science job outlook 2025: Actuaries' Survival Guide Ping Wang, Fred Szabo, 2024-02-02 Actuaries' Survival Guide: Navigating the Exam and Data Science, Third Edition explains what actuaries are, what they do, and where they do it. It describes exciting combinations of ideas, techniques, and skills involved in the day-to-day work of actuaries. This edition has been updated to reflect the rise of social networking and the internet, the progress toward a global knowledge-based economy, and the global expansion of the actuarial field that has occurred since the prior edition. - Includes details on the Society of Actuaries' (SOA) and Casualty Actuarial Society (CAS) examinations, as well as sample questions and answers - Presents an overview of career options and includes profiles of companies and agencies that employ actuaries - Provides a link between theory and practice and helps readers understand the blend of qualitative and quantitative skills and knowledge required to succeed in actuarial exams - Offers insights provided by real-life actuaries and actuarial students about the profession |
| data science job outlook 2025: Data Science and Computational Intelligence K. R. Venugopal, P. Deepa Shenoy, Rajkumar Buyya, L. M. Patnaik, Sitharama S. Iyengar, 2021-12-07 This book constitutes revised and selected papers from the Sixteenth International Conference on Information Processing, ICInPro 2021, held in Bangaluru, India in October 2021. The 33 full and 9 short papers presented in this volume were carefully reviewed and selected from a total of 177 submissions. The papers are organized in the following thematic blocks: Computing & Network Security; Data Science; Intelligence & IoT. |
| data science job outlook 2025: Artificial Intelligence in Banking Introbooks, 2020-04-07 In these highly competitive times and with so many technological advancements, it is impossible for any industry to remain isolated and untouched by innovations. In this era of digital economy, the banking sector cannot exist and operate without the various digital tools offered by the ever new innovations happening in the field of Artificial Intelligence (AI) and its sub-set technologies. New technologies have enabled incredible progression in the finance industry. Artificial Intelligence (AI) and Machine Learning (ML) have provided the investors and customers with more innovative tools, new types of financial products and a new potential for growth.According to Cathy Bessant (the Chief Operations and Technology Officer, Bank of America), AI is not just a technology discussion. It is also a discussion about data and how it is used and protected. She says, In a world focused on using AI in new ways, we're focused on using it wisely and responsibly. |
| data science job outlook 2025: Meeting Regional Stemm Workforce Needs in the Wake of Covid-19 National Academies of Sciences Engineering and Medicine, Policy and Global Affairs, Board on Higher Education and Workforce, 2021-07-23 The COVID-19 pandemic is transforming the global economy and significantly shifting workforce demand, requiring quick, adaptive responses. The pandemic has revealed the vulnerabilities of many organizations and regional economies, and it has accelerated trends that could lead to significant improvements in productivity, performance, and resilience, which will enable organizations and regions to thrive in the next normal. To explore how communities around the United States are addressing workforce issues laid bare by the COVID-19 pandemic and how they are taking advantage of local opportunities to expand their science, technology, engineering, mathematics, and medicine (STEMM) workforces to position them for success going forward, the Board of Higher Education and Workforce of the National Academies of Sciences, Engineering, and Medicine convened a series of workshops to identify immediate and near-term regional STEMM workforce needs in the wake of the COVID-19 pandemic. The workshop planning committee identified five U.S. cities and their associated metropolitan areas - Birmingham, Alabama; Boston, Massachusetts; Richmond, Virginia; Riverside, California; and Wichita, Kansas - to host workshops highlighting promising practices that communities can use to respond urgently and appropriately to their STEMM workforce needs. A sixth workshop discussed how the lessons learned during the five region-focused workshops could be applied in other communities to meet STEMM workforce needs. This proceedings of a virtual workshop series summarizes the presentations and discussions from the six public workshops that made up the virtual workshop series and highlights the key points raised during the presentations, moderated panel discussions and deliberations, and open discussions among the workshop participants. |
| data science job outlook 2025: Creating Characters & Plots , |
| data science job outlook 2025: Opportunities in Psychology Careers Charles M. Super, Donald Edwin Super, 2001 Offers job seekers useful information about a variety of careers in the field of psychology. This book includes training and education requirements, salary statistics, and professional and Internet resources. |
| data science job outlook 2025: Reinventing Rural Gregory M. Fulkerson, Alexander R. Thomas, 2016-10-19 Reinventing Rural is a collection of original research papers that examine the ways in which rural people and places are changing in the context of an urbanizing world. This includes exploring the role of the environment, the economy, and related issues such as tourism. While traditionally relying on primary sector work in agriculture, mining, natural resources, and the like, rural areas are finding new ways to sustain themselves. This involves a new emphasis on environmental protection, as one important strategy has been to capitalize on natural amenities to attract residents and tourists. Beyond improvements to the economy are general improvements to the quality-of-life in rural communities. Consistent with this, the volume focuses on the two cornerstones of education and health, considering current challenges and offering ideas for reinventing rural quality-of-life. |
| data science job outlook 2025: Law and Policy for the Quantum Age Chris Jay Hoofnagle, Simson L. Garfinkel, 2022-01-06 The Quantum Age cuts through the hype to demystify quantum technologies, their development paths, and the policy issues they raise. |
| data science job outlook 2025: The Future of Work Darrell M. West, 2018-05-15 Looking for ways to handle the transition to a digital economy Robots, artificial intelligence, and driverless cars are no longer things of the distant future. They are with us today and will become increasingly common in coming years, along with virtual reality and digital personal assistants. As these tools advance deeper into everyday use, they raise the question—how will they transform society, the economy, and politics? If companies need fewer workers due to automation and robotics, what happens to those who once held those jobs and don't have the skills for new jobs? And since many social benefits are delivered through jobs, how are people outside the workforce for a lengthy period of time going to earn a living and get health care and social benefits? Looking past today's headlines, political scientist and cultural observer Darrell M. West argues that society needs to rethink the concept of jobs, reconfigure the social contract, move toward a system of lifetime learning, and develop a new kind of politics that can deal with economic dislocations. With the U.S. governance system in shambles because of political polarization and hyper-partisanship, dealing creatively with the transition to a fully digital economy will vex political leaders and complicate the adoption of remedies that could ease the transition pain. It is imperative that we make major adjustments in how we think about work and the social contract in order to prevent society from spiraling out of control. This book presents a number of proposals to help people deal with the transition from an industrial to a digital economy. We must broaden the concept of employment to include volunteering and parenting and pay greater attention to the opportunities for leisure time. New forms of identity will be possible when the job no longer defines people's sense of personal meaning, and they engage in a broader range of activities. Workers will need help throughout their lifetimes to acquire new skills and develop new job capabilities. Political reforms will be necessary to reduce polarization and restore civility so there can be open and healthy debate about where responsibility lies for economic well-being. This book is an important contribution to a discussion about tomorrow—one that needs to take place today. |
| data science job outlook 2025: Big Data Computing Rajendra Akerkar, 2013-12-05 Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book introduces a broad range of Big Data concepts, tools, and techniques. It covers a wide range of research, and provides comparisons between state-of-the-art approaches. Comprised of five sections, the book focuses on: What Big Data is and why it is important Semantic technologies Tools and methods Business and economic perspectives Big Data applications across industries |
| data science job outlook 2025: The New Rules of Work Alexandra Cavoulacos, Kathryn Minshew, 2017 In this definitive guide to the ever-changing modern workplace, Kathryn Minshew and Alexandra Cavoulacos, the co-founders of popular career website TheMuse.com, show how to play the game by the New Rules. The Muse is known for sharp, relevant, and get-to-the-point advice on how to figure out exactly what your values and your skills are and how they best play out in the marketplace. Now Kathryn and Alex have gathered all of that advice and more in The New Rules of Work. Through quick exercises and structured tips, the authors will guide you as you sort through your countless options; communicate who you are and why you are valuable; and stand out from the crowd. The New Rules of Work shows how to choose a perfect career path, land the best job, and wake up feeling excited to go to work every day-- whether you are starting out in your career, looking to move ahead, navigating a mid-career shift, or anywhere in between-- |
| data science job outlook 2025: Enhanced Occupational Outlook Handbook Jist Works, 2008-07 Job seekers, students, and others doing in-depth career research can access information on nearly 8,000 jobs in one current, convenient book. With more job descriptions than in any other career reference, the best-selling Enhanced Occupational Outlook Handbook provides a practical way to obtain and use the information from the three most authoritative occupational data sources. It includes the complete text of the latest Occupational Outlook Handbook by the U.S. Department of Labor, plus related job descriptions from the government's latest O*NET database and from the Dictionary of Occupational Titles. Readers learn about all of their career options in one resource. Now in its all-new seventh edition, the EOOH is easy to use because it's organized by clusters of related jobs - the same user-friendly structure as in the OOH. Readers doing career research and planning also learn the latest details on earnings, job growth, education and skills required, working conditions, employment trends, and more. A new appendix organizes all the OOH jobs by personality codes so readers can easily find related job descriptions after using any career assessment based on Holland's six personality types (Realistic, Investigative, Artistic, Social, Enterprising, and Conventional). |
| data science job outlook 2025: Principles of Financial Engineering Robert Kosowski, Salih N. Neftci, 2014-11-26 Principles of Financial Engineering, Third Edition, is a highly acclaimed text on the fast-paced and complex subject of financial engineering. This updated edition describes the engineering elements of financial engineering instead of the mathematics underlying it. It shows how to use financial tools to accomplish a goal rather than describing the tools themselves. It lays emphasis on the engineering aspects of derivatives (how to create them) rather than their pricing (how they act) in relation to other instruments, the financial markets, and financial market practices. This volume explains ways to create financial tools and how the tools work together to achieve specific goals. Applications are illustrated using real-world examples. It presents three new chapters on financial engineering in topics ranging from commodity markets to financial engineering applications in hedge fund strategies, correlation swaps, structural models of default, capital structure arbitrage, contingent convertibles, and how to incorporate counterparty risk into derivatives pricing. Poised midway between intuition, actual events, and financial mathematics, this book can be used to solve problems in risk management, taxation, regulation, and above all, pricing. A solutions manual enhances the text by presenting additional cases and solutions to exercises. This latest edition of Principles of Financial Engineering is ideal for financial engineers, quantitative analysts in banks and investment houses, and other financial industry professionals. It is also highly recommended to graduate students in financial engineering and financial mathematics programs. - The Third Edition presents three new chapters on financial engineering in commodity markets, financial engineering applications in hedge fund strategies, correlation swaps, structural models of default, capital structure arbitrage, contingent convertibles and how to incorporate counterparty risk into derivatives pricing, among other topics - Additions, clarifications, and illustrations throughout the volume show these instruments at work instead of explaining how they should act - The solutions manual enhances the text by presenting additional cases and solutions to exercises |
| data science job outlook 2025: OECD Employment Outlook 2019 The Future of Work OECD, 2019-04-25 The 2019 edition of the OECD Employment Outlook presents new evidence on changes in job stability, underemployment and the share of well-paid jobs, and discusses the policy implications of these changes with respect to how technology, globalisation, population ageing, and other megatrends are transforming the labour market in OECD countries. |
| data science job outlook 2025: SWE , 2005 |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
