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| deloitte data science internship: Trustworthy AI Beena Ammanath, 2022-03-15 An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI. |
| deloitte data science internship: Business Chemistry Kim Christfort, Suzanne Vickberg, 2018-05-22 A guide to putting cognitive diversity to work Ever wonder what it is that makes two people click or clash? Or why some groups excel while others fumble? Or how you, as a leader, can make or break team potential? Business Chemistry holds the answers. Based on extensive research and analytics, plus years of proven success in the field, the Business Chemistry framework provides a simple yet powerful way to identify meaningful differences between people’s working styles. Who seeks possibilities and who seeks stability? Who values challenge and who values connection? Business Chemistry will help you grasp where others are coming from, appreciate the value they bring, and determine what they need in order to excel. It offers practical ways to be more effective as an individual and as a leader. Imagine you had a more in-depth understanding of yourself and why you thrive in some work environments and flounder in others. Suppose you had a clearer view on what to do about it so that you could always perform at your best. Imagine you had more insight into what makes people tick and what ticks them off, how some interactions unlock potential while others shut people down. Suppose you could gain people’s trust, influence them, motivate them, and get the very most out of your work relationships. Imagine you knew how to create a work environment where all types of people excel, even if they have conflicting perspectives, preferences and needs. Suppose you could activate the potential benefits of diversity on your teams and in your organizations, improving collaboration to achieve the group’s collective potential. Business Chemistry offers all of this--you don’t have to leave it up to chance, and you shouldn’t. Let this book guide you in creating great chemistry! |
| deloitte data science internship: Big Data at Work Thomas Davenport, 2014-02-04 Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource. |
| deloitte data science internship: Analytics and Big Data: The Davenport Collection (6 Items) Thomas H. Davenport, Jeanne G. Harris, 2014-08-12 The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics. |
| deloitte data science internship: Educational Perspectives on Digital Technologies in Modeling and Management Prakasha, G. S., Lapina, Maria, Balakrishnan, Deepanraj, Sajid, Mohammad, 2024-01-07 The complexity of managing and modeling various systems, from social networks to educational institutions and technical systems, has reached unprecedented levels. Traditional approaches struggle to keep pace with the dynamic nature of these challenges, leaving scholars, educators, and professionals searching for innovative solutions. This growing problem calls for a comprehensive guide to harnessing the potential of digital technologies for effective modeling and management. Educational Perspectives on Digital Technologies in Modeling and Management is a groundbreaking book that addresses the pressing need for modern solutions to keep up with the evolving challenges of modeling systems. This research book emerges from the collaborative efforts of teaching staff from leading universities, and years of dedicated scientific research and experimentation. It focuses on modeling complex systems using digital technologies, presenting fresh insights and innovative methodologies for academics, scholars, and aspiring professionals who are delving into the world of digitalization of economic processes and their management. The text caters to the specific needs of educators, IT professionals, and business analysts. Covering a wide array of topics, from information security to speaker verification and turbulent gas flow, this book serves as a valuable resource for a diverse audience seeking to excel in their respective fields. |
| deloitte data science internship: Deep Learning with TensorFlow 2 and Keras Antonio Gulli, Amita Kapoor, Sujit Pal, 2019-12-27 Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learnBuild machine learning and deep learning systems with TensorFlow 2 and the Keras APIUse Regression analysis, the most popular approach to machine learningUnderstand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiersUse GANs (generative adversarial networks) to create new data that fits with existing patternsDiscover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret anotherApply deep learning to natural human language and interpret natural language texts to produce an appropriate responseTrain your models on the cloud and put TF to work in real environmentsExplore how Google tools can automate simple ML workflows without the need for complex modelingWho this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems. Some knowledge of machine learning is expected. |
| deloitte data science internship: The Data Science Handbook Field Cady, 2017-02-28 A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon. |
| deloitte data science internship: Pandas Cookbook Theodore Petrou, 2017-10-23 Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysis About This Book Use the power of pandas to solve most complex scientific computing problems with ease Leverage fast, robust data structures in pandas to gain useful insights from your data Practical, easy to implement recipes for quick solutions to common problems in data using pandas Who This Book Is For This book is for data scientists, analysts and Python developers who wish to explore data analysis and scientific computing in a practical, hands-on manner. The recipes included in this book are suitable for both novice and advanced users, and contain helpful tips, tricks and caveats wherever necessary. Some understanding of pandas will be helpful, but not mandatory. What You Will Learn Master the fundamentals of pandas to quickly begin exploring any dataset Isolate any subset of data by properly selecting and querying the data Split data into independent groups before applying aggregations and transformations to each group Restructure data into tidy form to make data analysis and visualization easier Prepare real-world messy datasets for machine learning Combine and merge data from different sources through pandas SQL-like operations Utilize pandas unparalleled time series functionality Create beautiful and insightful visualizations through pandas direct hooks to Matplotlib and Seaborn In Detail This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced recipes combine several different features across the pandas library to generate results. Style and approach The author relies on his vast experience teaching pandas in a professional setting to deliver very detailed explanations for each line of code in all of the recipes. All code and dataset explanations exist in Jupyter Notebooks, an excellent interface for exploring data. |
| deloitte data science internship: Money for Graduate Students in the Social & Behavioral Sciences 2005-2007 Gail Ann Schlachter, R. David Weber, 2005-07 |
| deloitte data science internship: Vault Guide to the Top 25 Consulting Firms , 2013 The;Vault Guide to the Top 25 Consulting Firms, ;European Edition has arrived for 2014--the eighth edition of this invaluable career guide. |
| deloitte data science internship: Optimized C++ Kurt Guntheroth, 2016-04-27 In today’s fast and competitive world, a program’s performance is just as important to customers as the features it provides. This practical guide teaches developers performance-tuning principles that enable optimization in C++. You’ll learn how to make code that already embodies best practices of C++ design run faster and consume fewer resources on any computer—whether it’s a watch, phone, workstation, supercomputer, or globe-spanning network of servers. Author Kurt Guntheroth provides several running examples that demonstrate how to apply these principles incrementally to improve existing code so it meets customer requirements for responsiveness and throughput. The advice in this book will prove itself the first time you hear a colleague exclaim, “Wow, that was fast. Who fixed something?” Locate performance hot spots using the profiler and software timers Learn to perform repeatable experiments to measure performance of code changes Optimize use of dynamically allocated variables Improve performance of hot loops and functions Speed up string handling functions Recognize efficient algorithms and optimization patterns Learn the strengths—and weaknesses—of C++ container classes View searching and sorting through an optimizer’s eye Make efficient use of C++ streaming I/O functions Use C++ thread-based concurrency features effectively |
| deloitte data science internship: Data Science for Business Foster Provost, Tom Fawcett, 2013-07-27 Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the data-analytic thinking necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates |
| deloitte data science internship: Cool Infographics Randy Krum, 2013-10-23 Make information memorable with creative visual design techniques Research shows that visual information is more quickly and easily understood, and much more likely to be remembered. This innovative book presents the design process and the best software tools for creating infographics that communicate. Including a special section on how to construct the increasingly popular infographic resume, the book offers graphic designers, marketers, and business professionals vital information on the most effective ways to present data. Explains why infographics and data visualizations work Shares the tools and techniques for creating great infographics Covers online infographics used for marketing, including social media and search engine optimization (SEO) Shows how to market your skills with a visual, infographic resume Explores the many internal business uses of infographics, including board meeting presentations, annual reports, consumer research statistics, marketing strategies, business plans, and visual explanations of products and services to your customers With Cool Infographics, you'll learn to create infographics to successfully reach your target audience and tell clear stories with your data. |
| deloitte data science internship: Ten Types of Innovation Larry Keeley, Helen Walters, Ryan Pikkel, Brian Quinn, 2013-07-15 Innovation principles to bring about meaningful and sustainable growth in your organization Using a list of more than 2,000 successful innovations, including Cirque du Soleil, early IBM mainframes, the Ford Model-T, and many more, the authors applied a proprietary algorithm and determined ten meaningful groupings—the Ten Types of Innovation—that provided insight into innovation. The Ten Types of Innovation explores these insights to diagnose patterns of innovation within industries, to identify innovation opportunities, and to evaluate how firms are performing against competitors. The framework has proven to be one of the most enduring and useful ways to start thinking about transformation. Details how you can use these innovation principles to bring about meaningful—and sustainable—growth within your organization Author Larry Keeley is a world renowned speaker, innovation consultant, and president and co-founder of Doblin, the innovation practice of Monitor Group; BusinessWeek named Keeley one of seven Innovation Gurus who are changing the field The Ten Types of Innovation concept has influenced thousands of executives and companies around the world since its discovery in 1998. The Ten Types of Innovation is the first book explaining how to implement it. |
| deloitte data science internship: The Social Life of Information John Seely Brown, Paul Duguid, 2017-02-21 Understand the human place in a digital world. “Should be read by anyone interested in understanding the future,” The Times Literary Supplement raved about the original edition of The Social Life of Information. We’re now living in that future, and one of the seminal books of the Internet Age is more relevant than ever. The future was a place where technology was supposed to empower individuals and obliterate social organizations. Pundits predicted that information technology would spell the end of almost everything—from mass media to bureaucracies, universities, politics, and governments. Clearly, we are not living in that future. The Social Life of Information explains why. John Seely Brown and Paul Duguid show us how to look beyond mere information to the social context that creates and gives meaning to it. Arguing elegantly for the important role that human sociability plays, even—perhaps especially—in the digital world, The Social Life of Information gives us an optimistic look beyond the simplicities of information and individuals. It shows how a better understanding of the contribution that communities, organizations, and institutions make to learning, working, and innovating can lead to the richest possible use of technology in our work and everyday lives. With a new introduction by David Weinberger and reflections by the authors on developments since the book’s first publication, this new edition is essential reading for anyone seeking to understand the human place in a digital world. |
| deloitte data science internship: 25 Top Consulting Firms WetFeet (Firm), WetFeet, 2008 |
| deloitte data science internship: Colleges Worth Your Money Andrew Belasco, Dave Bergman, Michael Trivette, 2024-06-01 Colleges Worth Your Money: A Guide to What America's Top Schools Can Do for You is an invaluable guide for students making the crucial decision of where to attend college when our thinking about higher education is radically changing. At a time when costs are soaring and competition for admission is higher than ever, the college-bound need to know how prospective schools will benefit them both as students and after graduation. Colleges Worth Your Moneyprovides the most up-to-date, accurate, and comprehensive information for gauging the ROI of America’s top schools, including: In-depth profiles of 200 of the top colleges and universities across the U.S.; Over 75 key statistics about each school that cover unique admissions-related data points such as gender-specific acceptance rates, early decision acceptance rates, and five-year admissions trends at each college. The solid facts on career outcomes, including the school’s connections with recruiters, the rate of employment post-graduation, where students land internships, the companies most likely to hire students from a particular school, and much more. Data and commentary on each college’s merit and need-based aid awards, average student debt, and starting salary outcomes. Top Colleges for America’s Top Majors lists highlighting schools that have the best programs in 40+ disciplines. Lists of the “Top Feeder” undergraduate colleges into medical school, law school, tech, journalism, Wall Street, engineering, and more. |
| deloitte data science internship: Work Disrupted Jeff Schwartz, 2021-01-07 If you only read one book on the future of work, Work Disrupted: Opportunity, Resilience, and Growth in the Accelerated Future of Work should be that book. The future of work swept in sooner than expected, accelerated by Covid-19, creating an urgent need for new maps, new mindsets, new strategies-- and most importantly, a trusted guide to take us on this journey. That guide is Jeff Schwartz. A founding partner of Deloitte Consulting’s Future of Work practice, Schwartz brings clarity, humor, wisdom, and practical advice to the future of work, a topic surrounded by misinformation, fear, and confusion. With a fundamental belief in the power of human innovation and creativity, Schwartz presents the key issues, critical choices, and potential pitfalls that must be on everyone’s radar. If you're anxious about robots taking away your job in the future, you will take comfort in the realistic perspective, fact-based insights, and practical steps Schwartz offers. If you're not sure where to even begin to prepare, follow his level-headed advice and easy-to-follow action plans. If you're a business leader caught between keeping up, while also being thoughtful about the next moves, you will appreciate the playbook directed at you. If you're wondering how Covid-19 will change how and where you will work, Work Disrupted has you covered. Written in a conversational style by Schwartz, with Suzanne Riss, an award-winning journalist and book author, Work Disrupted offers a welcome alternative to books on the topic that lack a broad perspective or dwell on the problems rather than offer solutions. Timely and insightful, the book includes the impact of Covid-19 on our present and future work. Interviews with leading thinkers on the future of work offer additional perspectives and guidance.Cartoons created for the book by leading business illustrator Tom Fishburne bring to life the reader’s journey and the complex issues surrounding the topic. Told from the perspective of an economist, management advisor, and social commentator, Work Disrupted offers hope--and practical advice--exploring such topics as: How we frame what lies ahead is a critical navigational tool. Discover the signposts that can serve as practical guides for individuals who have families to support, mortgages to pay, and want to stay gainfully employed no matter what the future holds. The importance of recognizing the rapidly evolving opportunities in front of us. Learn how to build resilience—in careers, organizations, and leaders—for what lies ahead. Why exploring new mental models helps us discover the steps we need to take to thrive. Individuals can decide how to protect their livelihood while businesses and public institutions can consider how they can lead and support workforces to thrive in twenty-first-century careers and work. Jeff's marvelous book is a roadmap for the new world of work with clear signposts. His insights will help readers discover opportunities, take action, and find hope in uncertain times. The ideas are fresh, beautifully crafted, and immediately applicable. This is not only a book to be read, but savored and used. —Dave Ulrich, Rensis Likert Professor, Ross School of Business, University of Michigan; Partner, the RBL Group; Co-author Reinventing the Organization |
| deloitte data science internship: Developing Analytic Talent Vincent Granville, 2014-03-24 Learn what it takes to succeed in the the most in-demand tech job Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT professionals. Data science involves extracting, creating, and processing data to turn it into business value. With over 15 years of big data, predictive modeling, and business analytics experience, author Vincent Granville is no stranger to data science. In this one-of-a-kind guide, he provides insight into the essential data science skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common job interview questions, sample resumes, and source code. The applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. Complete with case studies, this book is a must, whether you're looking to become a data scientist or to hire one. Explains the finer points of data science, the required skills, and how to acquire them, including analytical recipes, standard rules, source code, and a dictionary of terms Shows what companies are looking for and how the growing importance of big data has increased the demand for data scientists Features job interview questions, sample resumes, salary surveys, and examples of job ads Case studies explore how data science is used on Wall Street, in botnet detection, for online advertising, and in many other business-critical situations Developing Analytic Talent: Becoming a Data Scientist is essential reading for those aspiring to this hot career choice and for employers seeking the best candidates. |
| deloitte data science internship: Data Mining and Predictive Analytics Daniel T. Larose, 2015-02-19 Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives. |
| deloitte data science internship: Case Interview Secrets Victor Cheng, 2012 Cheng, a former McKinsey management consultant, reveals his proven, insider'smethod for acing the case interview. |
| deloitte data science internship: Delivering on Digital William D. Eggers, 2016-06-07 The government reform expert and acclaimed author of The Solution Revolution presents a roadmap for navigating the digital government era. In October 2013, HealthCare.gov went live—and promptly crashed. Poor website design was getting in the way of government operations, and the need for digital excellence in public institutions was suddenly crystal clear. Hundreds of the tech industry’s best and brightest dedicated themselves to redesigning the government’s industrial-era frameworks as fully digital systems. But to take Washington into the 21st century, we have to start by imagining a new kind of government. Imagine prison systems that use digital technology to return nonviolent offenders promptly and securely into society. Imagine a veteran’s health care system built around delivering a personalized customer experience for every Vet. We now have the digital tools—such as cloud computing, mobile devices, and analytics—to stage a real transformation. Delivering on Digital provides the handbook to make it happen. A leading authority on government reform, William D. Eggers knows how we can use tech-savvy teams, strong leadership, and innovative practices to reduce the risks and truly achieve a digitally transformed government. |
| deloitte data science internship: The Power of Pull John Hagel, John Hagel III, John Seely Brown, Lang Davison, 2012-12-04 How we can effectively address our most pressing challenges in a rapidly changing and increasingly interdependent world. |
| deloitte data science internship: 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 |
| deloitte data science internship: 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. |
| deloitte data science internship: Machine Learning Bookcamp Alexey Grigorev, 2021-11-23 The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning. |
| deloitte data science internship: De novo Molecular Design Gisbert Schneider, 2013-10-10 Systematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, Proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules. A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for chemical probes and diagnostics, pesticides, and any other molecule designed to interact with a biological system. Numerous images and screenshots illustrate the many examples and method descriptions. With its broad and balanced coverage, this will be the firststop resource not only for medicinal chemists, biochemists and biotechnologists, but equally for bioinformaticians and molecular designers for many years to come. From the content: * Reaction-driven de novo design * Adaptive methods in molecular design * Design of ligands against multitarget profiles * Free energy methods in ligand design * Fragment-based de novo design * Automated design of focused and target family-oriented compound libraries * Molecular de novo design by nature-inspired computing * 3D QSAR approaches to de novo drug design * Bioisosteres in de novo design * De novo design of peptides, proteins and nucleic acid structures, including RNA aptamers and many more. |
| deloitte data science internship: Artificial Intelligence and the Future of Defense Stephan De Spiegeleire, Matthijs Maas, Tim Sweijs, 2017-05-17 Artificial intelligence (AI) is on everybody’s minds these days. Most of the world’s leading companies are making massive investments in it. Governments are scrambling to catch up. Every single one of us who uses Google Search or any of the new digital assistants on our smartphones has witnessed first-hand how quickly these developments now go. Many analysts foresee truly disruptive changes in education, employment, health, knowledge generation, mobility, etc. But what will AI mean for defense and security? In a new study HCSS offers a unique perspective on this question. Most studies to date quickly jump from AI to autonomous (mostly weapon) systems. They anticipate future armed forces that mostly resemble today’s armed forces, engaging in fairly similar types of activities with a still primarily industrial-kinetic capability bundle that would increasingly be AI-augmented. The authors of this study argue that AI may have a far more transformational impact on defense and security whereby new incarnations of ‘armed force’ start doing different things in novel ways. The report sketches a much broader option space within which defense and security organizations (DSOs) may wish to invest in successive generations of AI technologies. It suggests that some of the most promising investment opportunities to start generating the sustainable security effects that our polities, societies and economies expect may lie in in the realms of prevention and resilience. Also in those areas any large-scale application of AI will have to result from a preliminary open-minded (on all sides) public debate on its legal, ethical and privacy implications. The authors submit, however, that such a debate would be more fruitful than the current heated discussions about ‘killer drones’ or robots. Finally, the study suggests that the advent of artificial super-intelligence (i.e. AI that is superior across the board to human intelligence), which many experts now put firmly within the longer-term planning horizons of our DSOs, presents us with unprecedented risks but also opportunities that we have to start to explore. The report contains an overview of the role that ‘intelligence’ - the computational part of the ability to achieve goals in the world - has played in defense and security throughout human history; a primer on AI (what it is, where it comes from and where it stands today - in both civilian and military contexts); a discussion of the broad option space for DSOs it opens up; 12 illustrative use cases across that option space; and a set of recommendations for - especially - small- and medium sized defense and security organizations. |
| deloitte data science internship: The Solution Revolution William D. Eggers, Paul Macmillan, 2013-08-27 Government Alone Can’t Solve Society’s Biggest Problems World hunger. Climate change. Crumbling infrastructure. It’s clear that in today’s era of fiscal constraints and political gridlock, we can no longer turn to government alone to tackle these and other towering social problems. What’s required is a new, more collaborative and productive economic system. The Solution Revolution brings hope—revealing just such a burgeoning new economy where players from across the spectrum of business, government, philanthropy, and social enterprise converge to solve big problems and create public value. By erasing public-private sector boundaries, the solution economy is unlocking trillions of dollars in social benefit and commercial value. Where tough societal problems persist, new problem solvers are crowdfunding, ridesharing, app-developing, or impact-investing to design innovative new solutions for seemingly intractable problems. Providing low-cost health care, fighting poverty, creating renewable energy, and preventing obesity are just a few of the tough challenges that also represent tremendous opportunities for those at the vanguard of this movement. They create markets for social good and trade solutions instead of dollars to fill the gap between what government can provide and what citizens need. So what drives the solution economy? Who are these new players and how are their roles changing? How can we grow the movement? And how can we participate? Deloitte’s William D. Eggers and Paul Macmillan answer these questions and more, and they introduce us to the people and organizations driving the revolution—from edgy social enterprises growing at a clip of 15 percent a year, to megafoundations, to Fortune 500 companies delivering social good on the path to profit. Recyclebank, RelayRides, and LivingGoods are just a few of the innovative organizations you’ll read about in this book. Government cannot handle alone the huge challenges facing our global society—and it shouldn’t. We need a different economic paradigm that can flexibly draw on resources, combine efforts, and create value, while improving the lives of citizens. The Solution Revolution shows the way. |
| deloitte data science internship: Topics for Group Discussion Prof Shrikant Prasoon, 2017-09 There are no specific rules to prepare for a GD. And no one knows what the topic of GD is going to be. This book includes topics that are likely to be put by the Group Testing Officer before the candidates to gauge their personality and leadership qualities. It will be a good idea to keep yourself abreast with topics from: 1. Current Affairs - Current Affairs is something that you have to be thorough with. Understand the recent crises affecting the world, latest developmental initiatives, and important national & global events. 2. Historical topics- Have a fair knowledge about the history of India and the world. Having historical information will help you cite examples and make references whenever needed. 3. Sports, Arts & Literature - In these topics, try to have a decent idea about what is popular, who are the leaders in each area, the latest that has happened in these areas. 4. Data crunching - Do familiarize yourself with important data. Throwing in some data if required in your GD will definitely create an impression among the assessors. Speak with a measure of confidence on the given topic; and secure the nod of the evaluator. |
| deloitte data science internship: Realization 2020 Pooja Pruthi, 2021-03-17 REALIZATION 2020 is the crux of different events that happened during 2020. It is going to help you go through all the important events that happened in 2020. Pooja Pruthi has shared her thoughts and Learnings during 2020. 2020 was one unforgettable year and we cannot deny the fact that it has shown the true colors of life. This book will help you learn basic lifestyle and how you can build your personality by taking care of few things. Let's go back and revive what all happened and realize what all we have to take care of in future. |
| deloitte data science internship: The Final Battle of Life Divya Bhadouria, The actions and adventures revolving around our life is an admixture of both good and bad. It is not that we always win our battles, but also we learn to be further superior from our failures. The Final Battle of Life, presented by Souvik Sengupta, offers the readers a new perspective on how to overcome the hardships and reach to the glory of life. This book is compiled by Divya Bhadouria, in association with many co-authors. The co-authors present their viewpoints through their literary brilliance. This book offers a variety of short stories and poems based on the importance of life, to win the battles of life with patience and love; and to overcome the failures with hard work and dedication, and to achieve the confidence one requires to conquer all the battles of life. |
| deloitte data science internship: Working Mother , 2002-10 The magazine that helps career moms balance their personal and professional lives. |
| deloitte data science internship: SQL Pocket Guide Alice Zhao, 2021-08-26 If you use SQL in your day-to-day work as a data analyst, data scientist, or data engineer, this popular pocket guide is your ideal on-the-job reference. You'll find many examples that address the language's complexities, along with key aspects of SQL used in Microsoft SQL Server, MySQL, Oracle Database, PostgreSQL, and SQLite. In this updated edition, author Alice Zhao describes how these database management systems implement SQL syntax for both querying and making changes to a database. You'll find details on data types and conversions, regular expression syntax, window functions, pivoting and unpivoting, and more. Quickly look up how to perform specific tasks using SQL Apply the book's syntax examples to your own queries Update SQL queries to work in five different database management systems NEW: Connect Python and R to a relational database NEW: Look up frequently asked SQL questions in the How Do I? chapter |
| deloitte data science internship: Blockchain Melanie Swan, 2015-01-24 Bitcoin is starting to come into its own as a digital currency, but the blockchain technology behind it could prove to be much more significant. This book takes you beyond the currency (Blockchain 1.0) and smart contracts (Blockchain 2.0) to demonstrate how the blockchain is in position to become the fifth disruptive computing paradigm after mainframes, PCs, the Internet, and mobile/social networking. Author Melanie Swan, Founder of the Institute for Blockchain Studies, explains that the blockchain is essentially a public ledger with potential as a worldwide, decentralized record for the registration, inventory, and transfer of all assets—not just finances, but property and intangible assets such as votes, software, health data, and ideas. Topics include: Concepts, features, and functionality of Bitcoin and the blockchain Using the blockchain for automated tracking of all digital endeavors Enabling censorship?resistant organizational models Creating a decentralized digital repository to verify identity Possibility of cheaper, more efficient services traditionally provided by nations Blockchain for science: making better use of the data-mining network Personal health record storage, including access to one’s own genomic data Open access academic publishing on the blockchain This book is part of an ongoing O’Reilly series. Mastering Bitcoin: Unlocking Digital Crypto-Currencies introduces Bitcoin and describes the technology behind Bitcoin and the blockchain. Blockchain: Blueprint for a New Economy considers theoretical, philosophical, and societal impact of cryptocurrencies and blockchain technologies. |
| deloitte data science internship: Can I have a Chocolate Milkshake? Rajat Mishra, How would you feel if, one day, you wake up in a hospital to the faces of doctors and nurses? How would you react when you see your dreams shattering right in front of your eyes? And what would go through your mind when you’re barred from pursuing your passion? Crushed and devastated from within? Meet Lt. Siddhant, an epitome of courage and spirit, who woke up to all this one morning and yet remained composed, when told that his right arm has been amputated post a fateful accident. An average human would collapse, but Lt. Siddhant, an Indian Army officer asked, “Can I have a Chocolate Milkshake?” This is the true-story of Lt. Siddhant, who when asked to shed his Olive Greens thereafter, goes on to build a successful career in the corporate world and becomes an inspiration for many. But, how did he get there? How did he win his battle? “Can I have a Chocolate Milkshake?” is a riveting tale of a man overcoming his limitations, fighting against all odds, and emerging as a winner. |
| deloitte data science internship: 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. |
| deloitte data science internship: Learning Deep Learning Magnus Ekman, 2021-07-19 NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals. -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us. -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| deloitte data science internship: The Innovator's Dilemma Clayton M. Christensen, 2013-10-22 Named one of 100 Leadership & Success Books to Read in a Lifetime by Amazon Editors An innovation classic. From Steve Jobs to Jeff Bezos, Clay Christensen’s work continues to underpin today’s most innovative leaders and organizations. The bestselling classic on disruptive innovation, by renowned author Clayton M. Christensen. His work is cited by the world’s best-known thought leaders, from Steve Jobs to Malcolm Gladwell. In this classic bestseller—one of the most influential business books of all time—innovation expert Clayton Christensen shows how even the most outstanding companies can do everything right—yet still lose market leadership. Christensen explains why most companies miss out on new waves of innovation. No matter the industry, he says, a successful company with established products will get pushed aside unless managers know how and when to abandon traditional business practices. Offering both successes and failures from leading companies as a guide, The Innovator’s Dilemma gives you a set of rules for capitalizing on the phenomenon of disruptive innovation. Sharp, cogent, and provocative—and consistently noted as one of the most valuable business ideas of all time—The Innovator’s Dilemma is the book no manager, leader, or entrepreneur should be without. |
| deloitte data science internship: Data Management, Analytics and Innovation Neha Sharma, Amlan Chakrabarti, Valentina Emilia Balas, Alfred M. Bruckstein, 2021-09-19 This book presents the latest findings in the areas of data management and smart computing, machine learning, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Fifth International Conference on Data Management, Analytics and Innovation (ICDMAI 2021), held during January 15–17, 2021, in a virtual mode. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. |
Deloitte | World Economic Forum
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Aug 9, 2023 · This is backed up by Deloitte’s findings, which highlight the positive impact of remote work on health, work-life balance and relationships for many people. Three in four men …
Deloitte | World Economic Forum
Jun 28, 2023 · The World Economic Forum is an independent international organization committed to improving the state of the world by engaging business, political, academic and …
Earth Observation to Drive $3.8 Trillion in Economic Growth by …
May 7, 2024 · Amplifying the Global Value of Earth Observation, published in collaboration with Deloitte, integrates perspectives of a group of 40 industry, technology and climate leaders …
Transitioning to a Quantum-Secure Economy | World Economic …
Sep 13, 2022 · Quantum computing promises transformative simulation and modelling capabilities across a diverse range of industries. However, these advances in computational power will …
Global Business Leaders Support ESG Convergence by Committing …
Jan 26, 2021 · In August 2019, at the request of its IBC, the World Economic Forum collaborated with Deloitte, EY, KPMG and PwC in a project to identify a set of universal metrics and …
Amplifying the Global Value of Earth Observation - The World …
May 7, 2024 · By 2030, the economic opportunity afforded by Earth observation (EO) insights is projected to surpass $700 billion while directly contributing to the abatement of 2 gigatonnes of …
Earth observation will unlock huge value for these 6 sectors
May 7, 2024 · According to a new study by the World Economic Forum, in collaboration with Deloitte — Amplifying the Global Value of Earth Observation — the potential value-added from …
10 million reasons to invest in social enterprises
Jan 18, 2024 · Anna Marks, Global Chair of Deloitte, DTTL, emphasizes the significance of this compass: “Beyond the data and strategies provided in this report, it is a narrative of hope and a …
The cost of living is a top concern for Gen Z and millennials
May 19, 2023 · Cost of living was cited as the top concern in the Deloitte survey, with 35% of Gen Zs and 42% of millennials saying it was their biggest concern. The prospect of unemployment …
The Future of Jobs Report 2023 | World Economic Forum
Apr 30, 2023 · The Future of Jobs Report 2023 explores how jobs and skills will evolve over the next five years. This fourth edition of the series continues the analysis of employer …
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