Data Science Major Penn State

  data science major penn state: Innovative Practices in Teaching Information Sciences and Technology John M. Carroll,
  data science major penn state: Roundtable on Data Science Postsecondary Education National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Division on Engineering and Physical Sciences, Board on Science Education, Computer Science and Telecommunications Board, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, 2020-09-02 Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting.
  data science major penn state: Mathematical Omnibus D. B. Fuks, Serge Tabachnikov, 2007 The book consists of thirty lectures on diverse topics, covering much of the mathematical landscape rather than focusing on one area. The reader will learn numerous results that often belong to neither the standard undergraduate nor graduate curriculum and will discover connections between classical and contemporary ideas in algebra, combinatorics, geometry, and topology. The reader's effort will be rewarded in seeing the harmony of each subject. The common thread in the selected subjects is their illustration of the unity and beauty of mathematics. Most lectures contain exercises, and solutions or answers are given to selected exercises. A special feature of the book is an abundance of drawings (more than four hundred), artwork by an accomplished artist, and about a hundred portraits of mathematicians. Almost every lecture contains surprises for even the seasoned researcher.
  data science major penn state: Instructional Design for Teachers Alison A. Carr-Chellman, 2015-06-26 Instructional Design for Teachers, Second Edition focuses on the instructional design (ID) process specifically for K-12 teachers. The first edition introduced a new, common-sense model of instructional design to take K-12 teachers through the ID process step by step, with a special emphasis on preparing, motivating, and encouraging new and ongoing use of ID principles. This second edition includes new material on design in gaming, cybercharters, online classrooms, and flipped classrooms, as well as special considerations for the Common Core. Each chapter contains framing questions, common errors, easy-to-use rules of thumb, clearly stated outcomes, and examples showing ID in action. The basic model and its application within constructivism and user-design will help teachers adapt from a behavioral approach to a more open, student-centered design approach. Combining basics with strategies to implement this model in the most advanced instructional approaches, this book empowers teachers and learners to use good instructional design with the most recent research-based approaches to learning. Instructional Design for Teachers shows how ID principles can impact instructional moments in positive and practical ways. The book can be used for basic ID courses and introductory curriculum courses, and is accessible to in-service as well as pre-service teachers.
  data science major penn state: Data Science in R Deborah Nolan, Duncan Temple Lang, 2015-04-21 Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts
  data science major penn state: 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
  data science major penn state: Actuarial Mathematics Harry H. Panjer, American Mathematical Society, 1986 These lecture notes from the 1985 AMS Short Course examine a variety of topics from the contemporary theory of actuarial mathematics. Recent clarification in the concepts of probability and statistics has laid a much richer foundation for this theory. Other factors that have shaped the theory include the continuing advances in computer science, the flourishing mathematical theory of risk, developments in stochastic processes, and recent growth in the theory of finance. In turn, actuarial concepts have been applied to other areas such as biostatistics, demography, economic, and reliability engineering.
  data science major penn state: The Selected Works of George E. Andrews George E. Andrews, 2013 This volume provides George Andrews' background commentary and comprehensive assessment of years of research and developments within the field of integer partitions.
  data science major penn state: 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.
  data science major penn state: Drawdown Paul Hawken, 2017-04-18 • New York Times bestseller • The 100 most substantive solutions to reverse global warming, based on meticulous research by leading scientists and policymakers around the world “At this point in time, the Drawdown book is exactly what is needed; a credible, conservative solution-by-solution narrative that we can do it. Reading it is an effective inoculation against the widespread perception of doom that humanity cannot and will not solve the climate crisis. Reported by-effects include increased determination and a sense of grounded hope.” —Per Espen Stoknes, Author, What We Think About When We Try Not To Think About Global Warming “There’s been no real way for ordinary people to get an understanding of what they can do and what impact it can have. There remains no single, comprehensive, reliable compendium of carbon-reduction solutions across sectors. At least until now. . . . The public is hungry for this kind of practical wisdom.” —David Roberts, Vox “This is the ideal environmental sciences textbook—only it is too interesting and inspiring to be called a textbook.” —Peter Kareiva, Director of the Institute of the Environment and Sustainability, UCLA In the face of widespread fear and apathy, an international coalition of researchers, professionals, and scientists have come together to offer a set of realistic and bold solutions to climate change. One hundred techniques and practices are described here—some are well known; some you may have never heard of. They range from clean energy to educating girls in lower-income countries to land use practices that pull carbon out of the air. The solutions exist, are economically viable, and communities throughout the world are currently enacting them with skill and determination. If deployed collectively on a global scale over the next thirty years, they represent a credible path forward, not just to slow the earth’s warming but to reach drawdown, that point in time when greenhouse gases in the atmosphere peak and begin to decline. These measures promise cascading benefits to human health, security, prosperity, and well-being—giving us every reason to see this planetary crisis as an opportunity to create a just and livable world.
  data science major penn state: The Penn State Blue Band: A Century of Pride and Precision , Ten chapters follow, each devoted to a single decade covering the major events in the band's development over the next hundred years, such as the adoption of the name Blue Band in 1923.--BOOK JACKET.
  data science major penn state: A Graduate Course on Statistical Inference Bing Li, G. Jogesh Babu, 2019-08-02 This textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The authors have included a chapter on estimating equations as a means to unify a range of useful methodologies, including generalized linear models, generalized estimation equations, quasi-likelihood estimation, and conditional inference. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course.
  data science major penn state: Integrated Region-Based Image Retrieval James Z. Wang, 2001-05-31 The system is exceptionally robust to image alterations such as intensity variation, sharpness variation, intentional distortions, cropping, shifting, and rotation. These features are extremely important to biomedical image databases since visual features in the query image are not exactly the same as the visual features in the images in the database. Integrated Region-Based Image Retrieval is an excellent reference for researchers in the fields of image retrieval, multimedia, computer vision and image processing.--BOOK JACKET.
  data science major penn state: The Pig Book Citizens Against Government Waste, 2013-09-17 The federal government wastes your tax dollars worse than a drunken sailor on shore leave. The 1984 Grace Commission uncovered that the Department of Defense spent $640 for a toilet seat and $436 for a hammer. Twenty years later things weren't much better. In 2004, Congress spent a record-breaking $22.9 billion dollars of your money on 10,656 of their pork-barrel projects. The war on terror has a lot to do with the record $413 billion in deficit spending, but it's also the result of pork over the last 18 years the likes of: - $50 million for an indoor rain forest in Iowa - $102 million to study screwworms which were long ago eradicated from American soil - $273,000 to combat goth culture in Missouri - $2.2 million to renovate the North Pole (Lucky for Santa!) - $50,000 for a tattoo removal program in California - $1 million for ornamental fish research Funny in some instances and jaw-droppingly stupid and wasteful in others, The Pig Book proves one thing about Capitol Hill: pork is king!
  data science major penn state: Computer Science Handbook Allen B. Tucker, 2004-06-28 When you think about how far and fast computer science has progressed in recent years, it's not hard to conclude that a seven-year old handbook may fall a little short of the kind of reference today's computer scientists, software engineers, and IT professionals need. With a broadened scope, more emphasis on applied computing, and more than 70 chap
  data science major penn state: Data Science and Big Data Analytics EMC Education Services, 2014-12-19 Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!
  data science major penn state: Beyond Objectivism and Relativism Richard J. Bernstein, 2011-09-16 Drawing freely and expertly from Continental and analytic traditions, Richard Bernstein examines a number of debates and controversies exemplified in the works of Gadamer, Habermas, Rorty, and Arendt. He argues that a new conversation is emerging about human rationality—a new understanding that emphasizes its practical character and has important ramifications both for thought and action.
  data science major penn state: The Computer Is Down Evangelina Vigil-PiÐÑn, 1987-01-01 The Computer is Down is at once a celebration of the crystalline and silvery image of the modern city, its advanced technology and economic power, as well as an iconoclastic questioning of the values attendant to this late twentieth century monument of civilization. The poetÍs eye guides the reader beyond the blinding glitter and the dizzying pace of the ñspace cityî to focus on street and neighborhood life, on the common man in his adaptation ? happy or uneasy ? to what seems to be an increasingly dehumanizing urban environment. In The Computer Is Down, our Virgil leads us down into the bowels of the city, where inhabit the human detritus: the downtrodden, the ignored, the forgotten. And above, at street level, the beauty of people maintaining their culture and traditions, unknowingly resisting dehumanization, resounds above the din of the traffic, the air drill and the wrecking ball. Like the black teens swaggering up the block to their ñghetto blasterî radios and the retired ñrich folksî maids steadily marching to an internal, more profound beat, the common folk shall endure ? longer than the towers of Ozymandias.
  data science major penn state: Penn State Michael Bezilla, 1985 Chartered in 1855 as an agricultural college, Penn State was designated Pennsylvania's land-grant school soon after the passage of the Morrill Act in 1862. Through this federal legislation, the institution assumed a legal obligation to offer studies not only in agriculture but also in engineering and other utilitarian fields as well as liberal arts. By giving it land-grant status, the Commonwealth of Pennsylvania made the privately chartered Penn State a public instrumentality and assumed a responsibility to assist it in carrying out its work. However, the notion that higher education should have practical value was a novel one in the mid-nineteenth century, and Penn State experienced several decades of drift and uncertainty before winning the confidence of Pennsylvania's citizens and their political leaders. The story of Penn State in the twentieth century is one of continuous expansion in its three-fold mission: instruction, research, and extension. Engineering, agriculture, mineral industries, and science were early strengths; during the Great Depression, liberal arts matured. Further curricular diversification occurred after the Second World War, and a medical school and teaching hospital were added in the 1960s. Penn State was among the earliest land-grant schools to inaugurate extension programs in agriculture, engineering, and home economics. Indeed, the success of extension education indirectly led to the founding of the first branch campuses in the 1930s, from which evolved the extensive Commonwealth Campus system. The history of Penn State encompasses more than academics. It is the personal story of such able leaders as presidents Evan Pugh, George Atherton, and Milton Eisenhower, who saw not the institution that was but the one that could be. It is the story of the confusing and often frustrating relationship between the University and the state government. As much as anything else, it is the story of students, with ample attention given to the social as well as scholastic side of student life. All of this is placed in the context of the history of land-grant education and Pennsylvania's overall educational development. This is an objective, analytical, and at times critical account of Penn State from the earliest days to the 1980s. With hundreds of illustrations and interesting vignettes, this book is a visually exciting and human-oriented history of a major state university.
  data science major penn state: Handbook of Research on Data Science for Effective Healthcare Practice and Administration Noughabi, Elham Akhond Zadeh, Raahemi, Bijan, Albadvi, Amir, Far, Behrouz H., 2017-07-20 Data science has always been an effective way of extracting knowledge and insights from information in various forms. One industry that can utilize the benefits from the advances in data science is the healthcare field. The Handbook of Research on Data Science for Effective Healthcare Practice and Administration is a critical reference source that overviews the state of data analysis as it relates to current practices in the health sciences field. Covering innovative topics such as linear programming, simulation modeling, network theory, and predictive analytics, this publication is recommended for all healthcare professionals, graduate students, engineers, and researchers that are seeking to expand their knowledge of efficient techniques for information analysis in the healthcare professions.
  data science major penn state: Encyclopedia of Data Science and Machine Learning Wang, John, 2023-01-20 Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
  data science major penn state: Introduction to Biostatistics Ronald N. Forthofer, Eun Sul Lee, 2014-05-19 The Biostatistics course is often found in the schools of public Health, medical schools, and, occasionally, in statistics and biology departments. The population of students in these courses is a diverse one, with varying preparedness. Introduction to Biostatistics assumes the reader has at least two years of high school algebra, but no previous exposure to statistics is required. Written for individuals who might be fearful of mathematics, this book minimizes the technical difficulties and emphasizes the importance of statistics in scientific investigation. An understanding of underlying design and analysis is stressed. The limitations of the research, design and analytical techniques are discussed, allowing the reader to accurately interpret results. Real data, both processed and raw, are used extensively in examples and exercises. Statistical computing packages - MINITAB, SAS and Stata - are integrated. The use of the computer and software allows a sharper focus on the concepts, letting the computer do the necessary number-crunching. - Emphasizes underlying statistical concepts more than competing texts - Focuses on experimental design and analysis, at an elementary level - Includes an introduction to linear correlation and regression - Statistics are central: probability is downplayed - Presents life tables and survival analysis - Appendix with solutions to many exercises - Special instructor's manual with solution to all exercises
  data science major penn state: Science, Technology and Gender , 2007 This publication examines the pressing needs to increase women's participation in S & T careers and enable the sex-disaggregated data collection that is needed for research and to raise public awareness of gender issues. Data and analysis provided by the UIS highlight the need for reinforced efforts at the national and international levels.--Publisher's description.
  data science major penn state: Automobile Insurance Jean Lemaire, 2013-03-09 The mathematical theory of non-life insurance developed much later than the theory of life insurance. The problems that occur in the former field are far more intricate for several reasons: 1. In the field oflife insurance, the company usually has to pay a claim on the policy only once: the insured dies or the policy matures only once. It is with only a few particular types of policy (for instance, sickness insurance, when the insured starts working again after a period of sickness) that a valid claim can be made on a number of different occasions. On the other hand, the general rule in non-life insurance is that the policyholder is liable to be the victim of several losses (in automobile insurance, of course, but also in burglary and fire insurance, householders' comprehensive insurance, and so on). 2. In the field of life insurance, the amount to be paid by the company excluding any bonuses-is determined at the inception of the policy. For the various types of life insurance contracts, the sum payable on death or at maturity of the policy is known in advance. In the field of non-life insurance, the amount of a loss is a random variable: the cost of an automobile crash, the partial or totalloss of a building as a result of fire, the number and nature of injuries, and so forth.
  data science major penn state: Engineering Problems William Macgregor Wallace, 1914
  data science major penn state: The Statistical Analysis of Functional MRI Data Nicole Lazar, 2008-06-10 The study of brain function is one of the most fascinating pursuits of m- ern science. Functional neuroimaging is an important component of much of the current research in cognitive, clinical, and social psychology. The exci- ment of studying the brain is recognized in both the popular press and the scienti?c community. In the pages of mainstream publications, including The New York Times and Wired, readers can learn about cutting-edge research into topics such as understanding how customers react to products and - vertisements (“If your brain has a ‘buy button,’ what pushes it?”, The New York Times,October19,2004),howviewersrespondtocampaignads(“Using M. R. I. ’s to see politics on the brain,” The New York Times, April 20, 2004; “This is your brain on Hillary: Political neuroscience hits new low,” Wired, November 12,2007),howmen and womenreactto sexualstimulation (“Brain scans arouse researchers,”Wired, April 19, 2004), distinguishing lies from the truth (“Duped,” The New Yorker, July 2, 2007; “Woman convicted of child abuse hopes fMRI can prove her innocence,” Wired, November 5, 2007), and even what separates “cool” people from “nerds” (“If you secretly like Michael Bolton, we’ll know,” Wired, October 2004). Reports on pathologies such as autism, in which neuroimaging plays a large role, are also common (for - stance, a Time magazine cover story from May 6, 2002, entitled “Inside the world of autism”).
  data science major penn state: International Educational Development Program , 1969
  data science major penn state: The Ethical Algorithm Michael Kearns, Aaron Roth, 2020 Algorithms have made our lives more efficient and entertaining--but not without a significant cost. Can we design a better future, one in which societial gains brought about by technology are balanced with the rights of citizens? The Ethical Algorithm offers a set of principled solutions based on the emerging and exciting science of socially aware algorithm design.
  data science major penn state: Big Data at Work Scott Tonidandel, Eden B. King, Jose M. Cortina, 2015-11-06 The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.
  data science major penn state: Principles of Database Management Wilfried Lemahieu, Seppe vanden Broucke, Bart Baesens, 2018-07-12 Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.
  data science major penn state: Data Science for Undergraduates National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-11-11 Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.
  data science major penn state: Big Copyright Versus the People Martin Skladany, 2018-06-07 Extreme copyright produces extreme consumption: ten hours a day, lost to screens. This book takes back our culture and creativity.
  data science major penn state: The Source of the River Douglas S. Massey, Camille Z. Charles, Garvey Lundy, Mary J. Fischer, 2011-06-27 African Americans and Latinos earn lower grades and drop out of college more often than whites or Asians. Yet thirty years after deliberate minority recruitment efforts began, we still don't know why. In The Shape of the River, William Bowen and Derek Bok documented the benefits of affirmative action for minority students, their communities, and the nation at large. But they also found that too many failed to achieve academic success. In The Source of the River, Douglas Massey and his colleagues investigate the roots of minority underperformance in selective colleges and universities. They explain how such factors as neighborhood, family, peer group, and early schooling influence the academic performance of students from differing racial and ethnic origins and differing social classes. Drawing on a major new source of data--the National Longitudinal Survey of Freshmen--the authors undertake a comprehensive analysis of the diverse pathways by which whites, African Americans, Latinos, and Asians enter American higher education. Theirs is the first study to document the different characteristics that students bring to campus and to trace out the influence of these differences on later academic performance. They show that black and Latino students do not enter college disadvantaged by a lack of self-esteem. In fact, overconfidence is more common than low self-confidence among some minority students. Despite this, minority students are adversely affected by racist stereotypes of intellectual inferiority. Although academic preparation is the strongest predictor of college performance, shortfalls in academic preparation are themselves largely a matter of socioeconomic disadvantage and racial segregation. Presenting important new findings, The Source of the River documents the ongoing power of race to shape the life chances of America's young people, even among the most talented and able.
  data science major penn state: Emerging Non-Volatile Memories Seungbum Hong, Orlando Auciello, Dirk Wouters, 2014-11-18 This book is an introduction to the fundamentals of emerging non-volatile memories and provides an overview of future trends in the field. Readers will find coverage of seven important memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), Multiferroic RAM (MFRAM), Phase-Change Memories (PCM), Oxide-based Resistive RAM (RRAM), Probe Storage, and Polymer Memories. Chapters are structured to reflect diffusions and clashes between different topics. Emerging Non-Volatile Memories is an ideal book for graduate students, faculty, and professionals working in the area of non-volatile memory. This book also: Covers key memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), and Multiferroic RAM (MFRAM), among others. Provides an overview of non-volatile memory fundamentals. Broadens readers’ understanding of future trends in non-volatile memories.
  data science major penn state: Turfgrass Management Alfred Turgeon, John Kaminski, 2019-09-10 Turfgrass Management Edition 1.0 has been designed as a basic text for beginning students of turfgrass science and management. In covering the important features of turfgrass systems, interactions between and among system components, and principles of turfgrass management, it attempts to unlock some of the mysteries of turf and establish the role of cultural interventions for achieving specific objectives. Illustrations and images are used generously throughout the text to help students grasp concepts, processes, and relationships of importance in turfgrass systems. Each chapter concludes with a series of questions to test the reader's comprehension of the material. Turfgrass Management has been known as the most respected foundational text for students and professionals within the turfgrass industry. Published by Turfpath, LLC, it is now the most comprehensive and affordable book on the market.
  data science major penn state: The Bakhtin Circle David G. Shepherd, Craig Brandist, Galin Tihanov, 2004 This book is a collection of essays on the most important figures associated with the Bakhtin Circle. It offers new biographical material, valuable translations of important Russian texts, a timeline and extensive bibliographical references.
  data science major penn state: Big Data Support of Urban Planning and Management Zhenjiang Shen, Miaoyi Li, 2017-09-26 In the era of big data, this book explores the new challenges of urban-rural planning and management from a practical perspective based on a multidisciplinary project. Researchers as contributors to this book have accomplished their projects by using big data and relevant data mining technologies for investigating the possibilities of big data, such as that obtained through cell phones, social network systems and smart cards instead of conventional survey data for urban planning support. This book showcases active researchers who share their experiences and ideas on human mobility, accessibility and recognition of places, connectivity of transportation and urban structure in order to provide effective analytic and forecasting tools for smart city planning and design solutions in China.
  data science major penn state: Hegemonic War and Grand Strategy Aaron M. Zack, 2017 This book examines the thought of German international relations scholar Ludwig Dehio and his insight into the dynamics of hegemonic conflicts. It analyzes the various attempts to conquer the European continent from the Hellenistic period to the twentieth century and how these bids for power relate to contemporary American grand strategy.
  data science major penn state: Gendered Worlds Judy Root Aulette, Judith G. Wittner, 2012 In Gendered Worlds, Second Edition, authors Judy Root Aulette and Judith Wittner use the sociological imagination to explore gender relations throughout the world. They look at how concrete forms of gender, race, class, and sexual inequality operate transnationally; examine the impact of globalization on local and everyday life experiences; and identify how local actors re-imagine social possibilities, resist injustice, and work toward change. Integrating theory with empirical studies that are of particular interest to college students--including research on violence, sports, and sexuality--the authors make gender concepts genuinely interesting and accessible. They also demonstrate how students can think critically about gender, both within and beyond the classroom. Incorporating a broad range of pedagogical features, including boxed sections and end-of-chapter sections that focus on social movements, Gendered Worlds, Second Edition, is ideal for courses in sociology of gender, sociology of sex roles, and gender studies. New to this Edition * A new concluding chapter, Gender and Globalization, and an expanded Chapter 1 * A completely rewritten Chapter 4 featuring the most current research on gender and sexuality, particularly the gendered character of heterosexuality and heterosexual relationships * A reconceptualized Chapter 9 exploring illness as a function of a global division of labor by race, ethnicity, gender, and nation * More research on gender outside of the United States in every chapter * Additional coverage of race, intersectionality, masculinity, and transgender issues--
  data science major penn state: Introduction to Engineering Design Edsgn, 2008
EXPLORE Data Sciences - Pennsylvania State University
The program provides students with the technical fundamentals of data sciences and helps them develop the knowledge and skills needed to manage and analyze large-scale, unstructured data.

COMPUTATIONAL DATA SCIENCE - Pennsylvania State …
Jan 14, 2025 · # Course is an Entrance to Major (ETM) requirement ~ Prerequisites also includes one or more ETM course * Course requires a grade of C or better for the major STAT 184* …

Data Sciences, B.S. (Information Sciences and Technology)
Data Sciences is a field of study concerned with developing, applying, and validating methods, processes, systems, and tools for drawing useful knowledge, justifiable conclusions, and …

Data Science - Applied Data Sciences Option (DATSC BS-APPDS
Entrance to Major courses must be completed with a C or higher DS 305 (New for PSU start SU23) This flowchart has been designed to complement the current Suggested Academic Plan found at …

Data Sciences, B.S. (Science) - undergraduate.bulletins.psu.edu
DS 200 Introduction to Data Sciences necessary to be successful in the future and to thrive while living in interconnected contexts. General Education aids students in developing intellectual …

Penn State: First-Year Brochure - Undergraduate Admissions
With more than 275 majors and 18 academic colleges across our campuses, you’ll find your unique path too. Not all majors are offered at every campus, and some majors must be started and …

Bachelor of Science in Functional Data Analytics - Penn State …
The Bachelor of Science in Functional Data Analytics, offered 100% online through Penn State World Campus, is tailored to prepare you for a successful career as a data

DATA SCIENCES UNDERGRADUATE HANDBOOK
Our curriculum covers fundamental programming techniques and skills, broad knowledge of data science foundations, mathematical foundations of computing, and advanced topics in computing …

Data Sciences, B.S. (Engineering) - Pennsylvania State University
Data Sciences is a field of study concerned with developing, applying, and validating methods, processes, systems, and tools for drawing useful knowledge, justifiable conclusions, and …

Data Sciences, B.S. (Information Sciences and Technology)
Identify and incorporate relevant abstraction and domain knowledge to formulate data science problems in different application contexts. Design or adapt appropriate statistical, machine …

Data Sciences, B.S. (Science) - Pennsylvania State University
To access previous years' suggested academic plans, please visit the archive (https:// bulletins.psu.edu/undergraduate/archive/) to view the appropriate Undergraduate Bulletin …

DATA SCIENCES UNDERGRADUATE HANDBOOK
Our curriculum covers fundamental programming techniques and skills, broad knowledge of data science foundations, mathematical foundations of computing, and advanced topics in computing …

Data Science - Pennsylvania State University
This Handbook provides program information specifically for the undergraduate Computational Data Sciences major. It should be used as a supplement to the College of Engineering Undergraduate …

Graduate Program in Data Analytics - Penn State World Campus
“Penn State’s Business Analytics Graduate Certificate and optional Master’s in Data Analytics, delivered through Penn State World Campus, provide the perfect road map for new, passionate …

Data Sciences, B.S. (Information Sciences and Technology)
All incoming Schreyer Honors College first-year students at University Park will take ENGL 137H/CAS 137H in the fall semester and ENGL 138T/CAS 138T in the spring semester. These …

Data Sciences, B.S. (Engineering) - Pennsylvania State University
Integrate statistical concepts/methods and computational/ machine learning methods to discover the structure of data and build predictive models. Apply the principles of data management to …

FUNCTIONAL DATA ANALYTICS, B.S. - bulletins.psu.edu
Candidates must complete the degree requirements for their major and earn at least a 2.00 grade-point average for all courses completed within their degree program.

Social Data Analytics, B.S. - Pennsylvania State University
Social Data Analytics is an interdisciplinary major that prepares students to participate in both a research environment where “big data” is a major source of insight into social and political …

FUNCTIONAL DATA ANALYTICS, B.S. - bulletins.psu.edu
Functional Data Analytics is an interdisciplinary major that prepares students to be data professionals who are skilled communicators/ project managers capable of translating the results …

Data Sciences, B.S. (Science) - undergraduate.bulletins.psu.edu
Data Sciences, B.S. (Science) 1 DATA SCIENCES, B.S. (SCIENCE) Begin Campus: Any Penn State Campus End Campus: University Park Degree Requirements For the Bachelor of …

Data Sciences, B.S. (Information Sciences and Technology)
Data Sciences integrate aspects of Computer Science, Informatics, and Statistics to yield powerful data science methods, systems, tools, and best practices that find applications across a …

Data Sciences, B.S. (Science) - Pennsylvania State University
Statistical Modeling Data Sciences: Data Sciences, B.S. at University Park Campus The course series listed below provides only one of the many possible ways to move through this …

Data Sciences, B.S. (Engineering) - Pennsylvania State University
solve data sciences problems using modern data science methods, tools, and best practices for data management, data exploration, data integration, predictive modeling (using machine …

Data Sciences, B.S. (Information Sciences and Technology)
eberly-science/data-sciences-bs/#suggestedacademicplantext) The course series listed below provides only one of the many possible ways to move through this curriculum.

Computer Science, B.S. (Abington) - Pennsylvania State …
The Computer Science major provides a solid foundation in the areas of systems programming, algorithm design, artificial intelligence, and engineering large software systems using state-of …

Computer Science, B.S. (Behrend)
Intelligence and Data Science, and Web Services and Applications. The students will be required to analyze and solve a significant industry sponsored computer problem during the senior …

COMPUTER SCIENCE, B.S. (CAPITAL) - Pennsylvania State …
The Computer Science major provides a solid foundation in the areas of systems programming, algorithm design, artificial intelligence, and engineering large software systems using state-of …

Social Data Analytics, B.S. - Pennsylvania State University
For the Bachelor of Science degree in Social Data Analytics, a minimum of 120 credits is required: Requirement Credits General Education 45 Requirements for the Major 87 12 of the 45 credits …

FUNCTIONAL DATA ANALYTICS, B.S. - bulletins.psu.edu
Requirements for the Major Each student must earn at least a grade of C in each 300- and 400-level course in the major field. To graduate, a student enrolled in the major must earn a grade …