Linked Data Courseware

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Linked Data Courseware

Unlock the potential of Linked Data with our comprehensive courseware, designed for professionals and researchers keen on mastering data management, semantic web, and data interoperability. Tailored for diverse audiences, our course caters to: IT Professionals: Ideal for software developers, data managers, and system architects looking to integrate Linked Data into modern information systems. Data Scientists and Analysts: Perfect for individuals aiming to link data and extract insights from diverse sources using semantic technologies. Information Specialists: Librarians, information managers, and archivists interested in enhancing information searches and sharing cultural heritage using Linked Data. Researchers: Academics spanning various fields who wish to share data and establish connections between research outcomes. Students: Suited for students of computer science, information sciences, and related disciplines, seeking to enhance their knowledge of Linked Data for future careers. Organizational Data Managers: Individuals responsible for managing and integrating data within organizations, aiming to grasp Linked Data concepts for seamless data integration. Policymakers and Innovation Managers: Intended for those keen on understanding how Linked Data contributes to innovation, data sharing among organizations, and deriving value from data. In this engaging course, participants will: Understand Linked Data and Semantic Web: Explore the basics of RDF, URIs, and triple stores, and comprehend how they function in the realm of Linked Data. Create and Publish RDF Data: Learn to create simple RDF data and understand the methods for publishing and consuming it effectively. Master SPARQL for Semantic Queries: Delve into SPARQL, gaining the ability to conduct basic and complex semantic searches, enhancing your data querying skills. Real-world Applications of Linked Data: Discover practical applications across domains such as media, healthcare, government, and more, understanding the advantages of Linked Data for data interoperability. Hands-on Workshops and Networking: Engage in practical workshops, create RDF data with OSDE, publish it online, and explore the future trends in Linked Data, including rich snippets and graph data science. Join us in this enriching learning journey where you'll grasp the intricacies of Linked Data, empowering yourself with valuable skills for the evolving digital landscape. Enroll now and step into the future of data integration and semantic web technologies.
Deep Learning for Coders with fastai and PyTorch

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Open Data for Education

This volume comprises a collection of papers presented at an Open Data in Education Seminar and the LILE workshops during 2014-2015. In the first part of the book, two chapters give different perspectives on the current use of linked and open data in education, including the use of technology and the topics that are being covered. The second part of the book focuses on the specific, practical applications that are being put in place to exploit open and linked data in education today. The goal of this book is to provide a snapshot of current activities, and to share and disseminate the growing collective experience on open and linked data in education. This volume brings together research results, studies, and practical endeavors from initiatives spread across several countries around the world. These initiatives are laying the foundations of open and linked data in the education movement and leading the way through innovative applications.