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This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet. It is an easy-to-use and easy-to learn programming language that is freely available on Windows, Macintosh , and Linux computers. There are free downloadable copies of this book in various electronic formats and a self-paced free online course where you can explore the course materials. All the supporting materials for the book are available under open and remixable licenses. This book is designed to teach people to program even if they have no prior experience.
The Librarian’s Introduction to Programming Languages presents case studies and practical applications for using the top programming languages in library and information settings. The languages covered are JavaScript, PERL, PHP, SQL, Python, Ruby, C, C#, and Java.
Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website,, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors.
Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics: Exploring Information".There are free downloadable electronic copies of this book in various formats and supporting materials for the book at The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.
This book describes the experiences of building the open-source Sakai teaching and learning environment software. Sakai was founded by the University of Michigan, Indiana University, Stanford University, Massachusetts Institute of Technology, the Open Knowledge Initiative(OKI), and the uPortal Project. The Sakai project was funded by the Andrew W. Mellon Foundation, The William and Flora Hewlett Foundation, and over 100 Sakai partner schools and companies for over five million dollars over a two year period. The project was very ambitious with an almost impossible schedule for delivery. Almost nothing in the project went according to the plans and yet today, the Sakai software is in use at nearly 300 schools worldwide with three million daily users and a ten percent market share of research universities. Sakai competes with commercial products like Blackboard and Desire2Learn as well as other open source products like Moodle, OLAT and ATutor. This is the story of the successes and failures and recoveries along the way as well as the fun and stress as the project went forward from an insider's perspective.

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