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| dual degree mba and data science: Build a Career in Data Science Emily Robinson, Jacqueline Nolis, 2020-03-24 Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder |
| dual degree mba and data science: Big Data MBA Bill Schmarzo, 2015-12-11 Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions. |
| dual degree mba and data science: Applied Managerial Economics Modern Lectures, Incorporated, 2009-10 |
| dual degree mba and data science: Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions Matt Taddy, 2019-08-23 Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science. |
| dual degree mba and data science: Data Analysis for Business, Economics, and Policy Gábor Békés, Gábor Kézdi, 2021-05-06 A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data. |
| dual degree mba and data science: Biomedical Engineering Fundamentals Joseph D. Bronzino, Donald R. Peterson, 2014-12-17 Known as the bible of biomedical engineering, The Biomedical Engineering Handbook, Fourth Edition, sets the standard against which all other references of this nature are measured. As such, it has served as a major resource for both skilled professionals and novices to biomedical engineering. Biomedical Engineering Fundamentals, the first volume of the handbook, presents material from respected scientists with diverse backgrounds in physiological systems, biomechanics, biomaterials, bioelectric phenomena, and neuroengineering. More than three dozen specific topics are examined, including cardiac biomechanics, the mechanics of blood vessels, cochlear mechanics, biodegradable biomaterials, soft tissue replacements, cellular biomechanics, neural engineering, electrical stimulation for paraplegia, and visual prostheses. The material is presented in a systematic manner and has been updated to reflect the latest applications and research findings. |
| dual degree mba and data science: AI-Centric Modeling and Analytics Alex Khang, Vugar Abdullayev, Babasaheb Jadhav, Shashi Gupta, Gilbert Morris, 2023-12-06 This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, machine learning-aided models, Internet of Things-driven applications, and cybersecurity techniques in the era of Industrial Revolution 4.0. AI-Centric Modeling and Analytics: Concepts, Technologies, and Applications focuses on how to implement solutions using models and techniques to gain insights, predict outcomes, and make informed decisions. This book presents advanced AI-centric modeling and analysis techniques that facilitate data analytics and learning in various applications. It offers fundamental concepts of advanced techniques, technologies, and tools along with the concept of real-time analysis systems. It also includes AI-centric approaches for the overall innovation, development, and implementation of business development and management systems along with a discussion of AI-centric robotic process automation systems that are useful in many government and private industries. This reference book targets a mixed audience of engineers and business analysts, researchers, professionals, and students from various fields. |
| dual degree mba and data science: The Future of Management Education Stéphanie Dameron, Thomas Durand, 2017-01-25 This book discusses the new challenges facing Business Schools around the world with potential scenarios that may be envisioned for 2030 and strategies for stakeholders. Based on documented descriptions of competitive dynamics in the ‘business’ of business schools in a variety of countries, the authors highlight the fact that the ‘industry’ of management education is going through major changes such as new governance and business models, mergers and acquisitions, internationalization of faculty and students coexisting with entrenchment in local markets, ever more needs for financial resources, development of distant and blended learning, and increasing pressure for research output to boost rankings. With concerns surrounding the sustainability of current trends in faculty salary inflation, social acceptability of higher fees, cost of distance learning and the risk of an academic-industry divide around knowledge produced by management research, The Future of Management Education develops an analysis of business models and institution regulation. The two volumes cover the context of Business Schools in ten countries and grapples with the challenges they currently face. They specifically discuss foresight scenarios and strategic implications for stakeholders (Deans, faculty, students, prospective students, alumni, local businesses, corporations, government, accreditation bodies). |
| dual degree mba and data science: Data-Driven DEI Randal Pinkett, 2023-03-14 A practical blueprint for successful, measurable, and impactful DEI initiatives In Data-Driven DEI: The Tools and Metrics You Need to Measure, Analyze, and Improve Diversity, Equity, & Inclusion, Dr. Randal Pinkett, a renowned diversity, equity, and inclusion (DEI) thought leader delivers a practical and evidence-based blueprint to achieving lasting impact with your DEI initiatives. Dr. Pinkett has created a simple, step-by-step process to assess the current state of your DEI, analyze that data to create a personal and organizational action plan, and implement data-driven, science-based, and technology-enabled interventions for greater diversity, equity, and inclusion. The book provides: Tools and instruments to assess your personal preferences and competencies as well as your organizational culture, climate, policies, and practices Strategies and proven practices to mitigate bias, improve decision-making, foster innovation, and expand thinking preferences, cultural competence, inclusive leadership, allyship and more A library of measures, metrics, and key performance indicators (KPIs) to gauge progress, evaluate results and demonstrate impact An indispensable resource for individual contributors, managers, executives, founders, entrepreneurs, and other business leaders, Data-Driven DEI deserves a place on the bookshelf of any professional seeking to have a real-world impact that delivers personal and organizational results. |
| dual degree mba and data science: Why Data Science Projects Fail Douglas Gray, Evan Shellshear, 2024-09-05 The field of artificial intelligence, data science, and analytics is crippling itself. Exaggerated promises of unrealistic technologies, simplifications of complex projects, and marketing hype are leading to an erosion of trust in one of our most critical approaches to making decisions: data driven. This book aims to fix this by countering the AI hype with a dose of realism. Written by two experts in the field, the authors firmly believe in the power of mathematics, computing, and analytics, but if false expectations are set and practitioners and leaders don’t fully understand everything that really goes into data science projects, then a stunning 80% (or more) of analytics projects will continue to fail, costing enterprises and society hundreds of billions of dollars, and leading to non-experts abandoning one of the most important data-driven decision-making capabilities altogether. For the first time, business leaders, practitioners, students, and interested laypeople will learn what really makes a data science project successful. By illustrating with many personal stories, the authors reveal the harsh realities of implementing AI and analytics. |
| dual degree mba and data science: Competing on Analytics Thomas H. Davenport, Jeanne G. Harris, 2007-03-06 You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics. |
| dual degree mba and data science: 2010-2011 College Admissions Data Sourcebook West Edition , 2010-09 |
| dual degree mba and data science: College Admissions Data Sourcebook Midwest Edition Bound 2010-11 , 2010-09 |
| dual degree mba and data science: 2012-2013 College Admissions Data Sourcebook Northeast Edition , |
| dual degree mba and data science: An Introduction to Data Science With Python Jeffrey S. Saltz, Jeffrey M. Stanton, 2024-05-29 An Introduction to Data Science with Python by Jeffrey S. Saltz and Jeffery M. Stanton provides readers who are new to Python and data science with a step-by-step walkthrough of the tools and techniques used to analyze data and generate predictive models. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using Python-based Jupyter Notebooks. The techniques include making tables and data frames, computing statistics, managing data, creating data visualizations, and building machine learning models. Each chapter breaks down the process into simple steps and components so students with no more than a high school algebra background will still find the concepts and code intelligible. Explanations are reinforced with linked practice questions throughout to check reader understanding. The book also covers advanced topics such as neural networks and deep learning, the basis of many recent and startling advances in machine learning and artificial intelligence. With their trademark humor and clear explanations, Saltz and Stanton provide a gentle introduction to this powerful data science tool. Included with this title: LMS Cartridge: Import this title’s instructor resources into your school’s learning management system (LMS) and save time. Don′t use an LMS? You can still access all of the same online resources for this title via the password-protected Instructor Resource Site. |
| dual degree mba and data science: Getting Started with Data Science Murtaza Haider, 2015-12-14 Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon. |
| dual degree mba and data science: Recent Developments in Data Science and Business Analytics Madjid Tavana, Srikanta Patnaik, 2018-03-27 This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains. |
| dual degree mba and data science: The Economics of Data, Analytics, and Digital Transformation Bill Schmarzo, Dr. Kirk Borne, 2020-11-30 Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset Acquire implementable knowledge on digital transformation through 8 practical laws Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly Book Description In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization's digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon. What you will learn Train your organization to transition from being data-driven to being value-driven Navigate and master the big data business model maturity index Learn a methodology for determining the economic value of your data and analytics Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used Become aware of digital transformation misconceptions and pitfalls Create empowered and dynamic teams that fuel your organization's digital transformation Who this book is for This book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers. |
| dual degree mba and data science: Data Science Careers, Training, and Hiring Renata Rawlings-Goss, 2019-08-02 This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build. |
| dual degree mba and data science: Practical Data Analytics for Innovation in Medicine Gary D. Miner, Linda A. Miner, Scott Burk, Mitchell Goldstein, Robert Nisbet, Nephi Walton, Thomas Hill, 2023-02-08 Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today’s medical issues and basic research Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate |
| dual degree mba and data science: Common Data Sense for Professionals Rajesh Jugulum, 2022-01-27 Data is an intrinsic part of our daily lives. Everything we do is a data point. Many of these data points are recorded with the intent to help us lead more efficient lives. We have apps that track our workouts, sleep, food intake, and personal finance. We use the data to make changes to our lives based on goals we have set for ourselves. Businesses use vast collections of data to determine strategy and marketing. Data scientists take data, analyze it, and create models to help solve problems. You may have heard of companies having data management teams or chief information officers (CIOs) or chief data officers (CDOs), etc. They are all people who work with data, but their function is more related to vetting data and preparing it for use by data scientists. The jump from personal data usage for self-betterment to mass data analysis for business process improvement often feels bigger to us than it is. In turn, we often think big data analysis requires tools held only by advanced degree holders. Although advanced degrees are certainly valuable, this book illustrates how it is not a requirement to adequately run a data science project. Because we are all already data users, with some simple strategies and exposure to basic analytical software programs, anyone who has the proper tools and determination can solve data science problems. The process presented in this book will help empower individuals to work on and solve data-related challenges. The goal of this book is to provide a step-by-step guide to the data science process so that you can feel confident in leading your own data science project. To aid with clarity and understanding, the author presents a fictional restaurant chain to use as a case study, illustrating how the various topics discussed can be applied. Essentially, this book helps traditional businesspeople solve data-related problems on their own without any hesitation or fear. The powerful methods are presented in the form of conversations, examples, and case studies. The conversational style is engaging and provides clarity. |
| dual degree mba and data science: 2012-2013 College Admissions Data Sourcebook Midwest Edition , |
| dual degree mba and data science: Developing Effective Educational Experiences through Learning Analytics Anderson, Mark, 2016-04-07 The quality of students’ learning experiences is a critical concern for all higher education institutions. With the assistance of modern technological advances, educational establishments have the capability to better understand the strengths and weaknesses of their learning programs. Developing Effective Educational Experiences through Learning Analytics is a pivotal reference source that focuses on the adoption of data mining and analysis techniques in academic institutions, examining how this collected information is utilized to improve the outcome of student learning. Highlighting the relevance of data analytics to current educational practices, this book is ideally designed for researchers, practitioners, and professionals actively involved in higher education settings. |
| dual degree mba and data science: Machine Learning for Business Analytics Galit Shmueli, Peter C. Bruce, Peter Gedeck, Inbal Yahav, Nitin R. Patel, 2023-03-22 MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using R An expanded chapter focused on discussion of deep learning techniques A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology. |
| dual degree mba and data science: Enhancing Effective Instruction and Learning Using Assessment Data Hong Jiao, Robert W. Lissitz, 2021 This book introduces theories and practices for using assessment data to enhance learning and instruction. Topics include reshaping the homework review process, iterative learning engineering, learning progressions, learning maps, score report designing, the use of psychosocial data, and the combination of adaptive testing and adaptive learning. In addition, studies proposing new methods and strategies, technical details about the collection and maintenance of process data, and examples illustrating proposed methods and/or software are included. Chapter 1, 4, 6, 8, and 9 discuss how to make valid interpretations of results and/or achieve more efficient instructions from various sources of data. Chapter 3 and 7 propose and evaluate new methods to promote students' learning by using evidence-based iterative learning engineering and supporting the teachers' use of assessment data, respectively. Chapter 2 provides technical details on the collection, storage, and security protection of process data. Chapter 5 introduces software for automating some aspects of developmental education and the use of predictive modeling. Chapter 10 describes the barriers to using psychosocial data for formative assessment purposes. Chapter 11 describes a conceptual framework for adaptive learning and testing and gives an example of a functional learning and assessment system. In summary, the book includes comprehensive perspectives of the recent development and challenges of using test data for formative assessment purposes. The chapters provide innovative theoretical frameworks, new perspectives on the use of data with technology, and how to build new methods based on existing theories. This book is a useful resource to researchers who are interested in using data and technology to inform decision making, facilitate instructional utility, and achieve better learning outcomes-- |
| dual degree mba and data science: College Admissions Data Sourcebook Northeast Edition Looseleaf 2010-11 , 2010-09 |
| dual degree mba and data science: The Best 294 Business Schools Princeton Review (Firm), 2011 Provides a detailed overview of the best business schools across North America, including information on each school's academic program, competitiveness, financial aid, admissions requirements, and social scenes. |
| dual degree mba and data science: Outsmarting AI Brennan Pursell, Joshua Walker, 2020-08-15 From factories to smartphones, Artificial Intelligence is already taking over. Outsmarting AI is not a how-to guide on making AI work, but making it work for YOU to boost profits and productivity. Each development in Artificial Intelligence (AI) technology brings about apprehension and panic for the future of society and for business. We’re bombarded with stories about the impending human-less workplace; it is no longer a question if man can be replaced by machine in certain tasks, but when. However, AI was not manufactured to destroy life as we know it. These emerging technologies were developed and are constantly updating with a particular goal in mind: optimization. AI feeds on data and information to improve outputs and increase potential. With this enhanced productivity, profit and productivity will be sure to follow. Written by Brennan Pursell, a business consultant and professor who hates jargon, and Joshua Walker, an AI pioneer with 18 years of experience in solutions and applications, Outsmarting AI is the first plain-English how-to guide on adapting AI for the non-coding proficient business leader. This book will help readers to Cut through the fog of AI hype See exactly what AI can actually do for people in business Identify the areas of their organization in most need of AI tools Prepare and control their data – AI is useless without it Adopt AI and develop the right culture to support it Track the productivity boost, cost savings, and increased profits Manage and minimize the threat of crippling lawsuits |
| dual degree mba and data science: Life Science Management Avo Schönbohm, Hans Henning von Horsten, Philipp Plugmann, 2022-07-14 The COVID-19 pandemic has reminded us of how important the life science industry is, and compels us to find efficient management methods specific to the industry. Pharmaceuticals, drug and vaccine development labs, R&D labs, medical instrumentation, and tech companies, hygiene supply companies, medical distribution chains, all form an integral part of this industry. At the interface of scientific research, technology, innovation and management and embedded in regulatory and legal frameworks, life science management is still an under-researched field of practice and science. This edited volume addresses this research gap and offers a wide range of practical and theoretical contributions that provide insights into one of the most exciting industries. The book is primarily directed at practitioners and decision makers in the life science industry. Students and professionals of life science management at all levels as well as policy makers will find valuable insights and inspiration for their daily work and career development. |
| dual degree mba and data science: Handbook of Research on Future Opportunities for Technology Management Education Khan, Basheer Ahmed, Kuofie, Matthew H. S., Suman, Sonika, 2021-06-25 Technology management education and business education are visibly intertwined in the current educational system. Certain efforts that have taken place in the recent past are the interinstitutional discourse around the world. Technology management is a dynamic and evolving profession, driven by changes in technology, globalization, sustainability, and the increasing importance of the service economy. The Handbook of Research on Future Opportunities for Technology Management Education is a comprehensive reference book that enables readers to comprehend the trends in technological changes and the need to orient business education and technology management in workplaces. The book serves to support with the formation and implementation of appropriate policies for technology management. Covering topics such as big data analytics, cloud computing adoption, and massive open online courses (MOOCs), this text is an essential resource for managers, technologists, teachers, executives, instructional designers, libraries, university researchers, students, faculty, and industry taught leaders. |
| dual degree mba and data science: Implications of Artificial Intelligence for Cybersecurity National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Intelligence Community Studies Board, Computer Science and Telecommunications Board, 2019-12-27 In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop. |
| dual degree mba and data science: Get Paid What You're Worth Robin L. Pinkley, Gregory B. Northcraft, 2014-09-02 In Get Paid What You're Worth, Robin L. Pinkley and Greogry B. Northcraft tell you how you can begin getting paid what you're worth--today! Couldn't you use more money? Whether you're entering the workforce for the first time, making a job change, or seeking better compensation for your contributions, Robin L. Pinkley and Gregory B. Northcraft will guide you step-by-step toward getting exactly what you deserve. - Learn why there may be more money available for you than you think. - Get the confidence to turn your strategic thinking into specific action. - Benefit from a panel of negotiations experts and their decades of experience. Applicants who negotiate job offers receive salaries and benefits of significantly more value than those who do not. And the compensation package you negotiate today will affect all your future job offers. Shouldn't it be the best that it can be? Get Paid What You're Worth is the handbook you need to successfully navigate the business of negotiation. |
| dual degree mba and data science: Research in Biological and Medical Sciences Walter Reed Army Institute of Research, 1973 |
| dual degree mba and data science: Computational Technology for Effective Health Care National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on Engaging the Computer Science Research Community in Health Care Informatics, 2009-03-24 Despite a strong commitment to delivering quality health care, persistent problems involving medical errors and ineffective treatment continue to plague the industry. Many of these problems are the consequence of poor information and technology (IT) capabilities, and most importantly, the lack cognitive IT support. Clinicians spend a great deal of time sifting through large amounts of raw data, when, ideally, IT systems would place raw data into context with current medical knowledge to provide clinicians with computer models that depict the health status of the patient. Computational Technology for Effective Health Care advocates re-balancing the portfolio of investments in health care IT to place a greater emphasis on providing cognitive support for health care providers, patients, and family caregivers; observing proven principles for success in designing and implementing IT; and accelerating research related to health care in the computer and social sciences and in health/biomedical informatics. Health care professionals, patient safety advocates, as well as IT specialists and engineers, will find this book a useful tool in preparation for crossing the health care IT chasm. |
| dual degree mba and data science: British Qualifications 2020 Kogan Page Editorial, 2019-12-03 Now in its 50th edition, British Qualifications 2020 is the definitive one-volume guide to every recognized qualification on offer in the United Kingdom. With an equal focus on both academic and professional vocational studies, this indispensable guide has full details of all institutions and organizations involved in the provision of further and higher education, making it the essential reference source for careers advisers, students, and employers. It also contains a comprehensive and up-to-date description of the structure of further and higher education in the UK, including an explanation of the most recent education reforms, providing essential context for the qualifications listed. British Qualifications 2020 is compiled and checked annually to ensure the highest currency and accuracy of this valuable information. Containing details on the professional vocational qualifications available from over 350 professional institutions and accrediting bodies, informative entries for all UK academic universities and colleges, and a full description of the current structural and legislative framework of academic and vocational education, it is the complete reference for lifelong learning and continuing professional development in the UK. |
| dual degree mba and data science: Computerworld , 1987-11-02 For more than 40 years, Computerworld has been the leading source of technology news and information for IT influencers worldwide. Computerworld's award-winning Web site (Computerworld.com), twice-monthly publication, focused conference series and custom research form the hub of the world's largest global IT media network. |
| dual degree mba and data science: Managers Not MBAs Henry Mintzberg, 2005-06-02 In this sweeping critique of how managers are educated and how, as a consequence, management is practiced, Henry Mintzberg offers thoughtful and controversial ideas for reforming both. “The MBA trains the wrong people in the wrong ways with the wrong consequences,” Mintzberg writes. “Using the classroom to help develop people already practicing management is a fine idea, but pretending to create managers out of people who have never managed is a sham.” Leaders cannot be created in a classroom. They arise in context. But people who already practice management can significantly improve their effectiveness given the opportunity to learn thoughtfully from their own experience. Mintzberg calls for a more engaging approach to managing and a more reflective approach to management education. He also outlines how business schools can become true schools of management. |
| dual degree mba and data science: Handbook of Research on Consumer Behavior Change and Data Analytics in the Socio-Digital Era Keikhosrokiani, Pantea, 2022-06-24 The emergence of new technologies within the industrial revolution has transformed businesses to a new socio-digital era. In this new era, businesses are concerned with collecting data on customer needs, behaviors, and preferences for driving effective customer engagement and product development, as well as for crucial decision making. However, the ever-shifting behaviors of consumers provide many challenges for businesses to pinpoint the wants and needs of their audience. The Handbook of Research on Consumer Behavior Change and Data Analytics in the Socio-Digital Era focuses on the concepts, theories, and analytical techniques to track consumer behavior change. It provides multidisciplinary research and practice focusing on social and behavioral analytics to track consumer behavior shifts and improve decision making among businesses. Covering topics such as consumer sentiment analysis, emotional intelligence, and online purchase decision making, this premier reference source is a timely resource for business executives, entrepreneurs, data analysts, marketers, advertisers, government officials, social media professionals, libraries, students and educators of higher education, researchers, and academicians. |
| dual degree mba and data science: Building Organizational Resilience With Neuroleadership Saluja, Shefali, Kukreja, Jyoti, Sharma, Sandhir, 2024-04-04 In today's landscape of leadership and management, a pressing issue confronts professionals at all levels. Traditional leadership paradigms, including emotional intelligence, are proving insufficient in meeting the demands of the dynamic professional environment. Leaders, both aspiring and experienced, grapple with the challenge of establishing deeper, more meaningful connections in both personal and professional spheres. What exacerbates this issue is the lack of awareness regarding the untapped potential residing at the intersection of neuroscience, cognitive psychology, and social sciences. Building Organizational Resilience With Neuroleadership serves as a beacon of knowledge and a solution to this enduring challenge. This thought-provoking book embarks on an illuminating journey through the emerging field of neuroleadership, seamlessly integrating insights from neuroscience, cognitive psychology, and leadership studies. It offers a comprehensive solution, meticulously crafted for academic scholars, researchers, management students, and seasoned professionals who aspire to transcend their leadership abilities. This groundbreaking book propels emotional intelligence to new heights, empowering leaders to forge more profound connections within their teams and organizations. By unraveling the neural underpinnings of effective leadership, it equips readers with the tools to recognize and manage emotions, thereby fostering authenticity in their interactions. It also reveals the profound influence of neurons, encouraging both budding and seasoned leaders to embrace the extraordinary role of brain functions in shaping magnetic organizational cultures and teams. By bringing together the collaborative efforts of pioneering researchers, social scientists, and behavioral experts, a wholistic solution is prepared within the pages of this text. |
| dual degree mba and data science: Two Cheers for Higher Education Steven Brint, 2020-08-04 Crusing student debt, rapidly eroding state funding, faculty embroiled in speech controversies, a higher-education market disrupted by online competition--today's headlines suggest that universities' power to advance knowledge and shape American society is rapidly declining. But after a recent period that witnessed soaring student enrollement and ample research funding, author Steven Brint argues that universities are in a better position than ever before. Focusing on the years 1980-2015, Brint details the trajectory of American universities, which was influenced by evolving standards of disciplinary professionalism, market-driven partnerships, and the goal of social inclusion. Today, knowledge-driven industries generate almost half of U.S. GDP, but students flock increasingly to fields connected to power centers of American life and steer away from the liberal arts. And opportunities for economic mobility are expanding even as academic expectations decline. In describing how universities can meet such challenges head on, especially in improving classroom learning, Brint offers not only a clear-eyed perspective on the current state of American higher education but also a pragmatically optimistic vision for the future. -- From publisher's description. |
Marvel Rivals Console/Controller Settings Guide 2025
Dec 27, 2024 · Aim Response Curve Type: Determines how your controller responds when you tilt your right analog stick. You have a choice between Dual-Zone (the new …
Best armour and augments for Dual Guns + Longsword build
Apr 18, 2025 · Tc did specifically mention blossom dance. And resistances aren't important when using ghost walker/factory, which I assume he is given the dual guns. …
Conditions for Dual Ultimates? - Dragon Ball: Xenoverse 2 - GameF…
As long as the custom partner has the Dual Ultimate equipped, they will use it every so often and then you can do the input for the second part of the attack no matter what …
Can I dual wield? - The Elder Scrolls IV: Oblivion - GameFAQs
Sep 10, 2007 · At stage 25 of The Path of Dawn quest, it is scripted for no apparent reason for Martin Septim to have a Lesser Staff of Lightning removed from his …
Character Creation - Icewind Dale: Enhanced Edition ... - GameFAQs
Apr 30, 2021 · For two-class combinations, dual-classing from Fighter is slightly better than multiclassing because dual-classing gives Grand Mastery, more HP and faster …
Marvel Rivals Console/Controller Settings Guide 2025
Dec 27, 2024 · Aim Response Curve Type: Determines how your controller responds when you tilt your right analog stick. You have a choice between Dual-Zone (the new default Overwatch …
Best armour and augments for Dual Guns + Longsword build
Apr 18, 2025 · Tc did specifically mention blossom dance. And resistances aren't important when using ghost walker/factory, which I assume he is given the dual guns. Yup I want to abuse …
Conditions for Dual Ultimates? - Dragon Ball: Xenoverse 2
As long as the custom partner has the Dual Ultimate equipped, they will use it every so often and then you can do the input for the second part of the attack no matter what you have equipped. …
Can I dual wield? - The Elder Scrolls IV: Oblivion - GameFAQs
Sep 10, 2007 · At stage 25 of The Path of Dawn quest, it is scripted for no apparent reason for Martin Septim to have a Lesser Staff of Lightning removed from his inventory, even though, …
Character Creation - Icewind Dale: Enhanced Edition
Apr 30, 2021 · For two-class combinations, dual-classing from Fighter is slightly better than multiclassing because dual-classing gives Grand Mastery, more HP and faster level gain. …
Resident Evil: Director's Cut Walkthrough & Guide - GameFAQs
Mar 24, 2024 · The Director's Cut is the first version of the original Resident Evil that I had played and the one I like best. While the Dual Shock edition that followed adds functionality to the …
Differences between original and Dual Shock versions?
My bad, in regards to the Ink Ribbons... to be really specific, in both modes of the original Director's Cut and in Arrange Mode in the Dual Shock version, you get 3 ribbons each pickup. …
Character Creation - Baldur's Gate: Enhanced Edition
Apr 21, 2024 · Multiclass vs. Dual Class There is a subtle distinction between multiclass characters and dual-class characters. The idea of playing an A / B multiclass character (for …
Ideal build for Rush for the first playthrough
For me I'm just going for a dual-wield build. Probably a ninja if I can get the requirements for it down. I was BR25 at The Fallen on PC and I got Rush to Ninja about halfway through. Now …
Some suggestions after 20+ hours for those still struggling
Oct 26, 2024 · Dual Gunner (Tech): fire-infused attack; Quadrastrike (Tech): high-BP damage (perfect for United Attack) Heeled Sandals (Legs): allows you to use a special kick attack …
