Web of Data
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Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Intermediate
- Deadline
- Flexible
- Duration
- 18 hours
- Certificate
- Paid Certificate Available
- Course author
- Catherine Faron Zucker
Description
This MOOC – a joint initiative between EIT Digital, Université de Nice Sophia-Antipolis / Université Côte d'Azur, and INRIA - introduces the Linked Data standards and principles that provide the foundation of the Semantic web. You will learn how to publish, obtain and use structured data directly from the Web. Learning the principles, languages, and standards to exchange data on the Web will enable you to design and produce new applications, products, and services that leverage the volume and variety of data the Web holds.We divided this course into four parts that cover the core technical skills and competencies you need to master to be able to use the Web as a space for giant structure data exchange:
• in the first part, “Principals of a Web of Linked Data”: you will learn and practice the principles to publish and obtain data directly on the Web instead of Web pages;
• in the second part, “The RDF Data Model”: you will learn the standard data model for the Web and its syntaxes to publish and link data on the Web in your applications and services;
• in the third part, “SPARQL Query Language”: you will learn how to directly query and access data sources on the Web and obtain structured data relevant to your activity and domain;
• in the fourth and final part, “Integration of other Data Formats and Sources”: you will learn how the Web standards interact and interoperate with other data formats to allow the integration of a variety of data sources.
Each week alternates short videos and quizzes, as well as supplementary resources and forums to gradually progress through the different principles and standards.
After following this course successfully, you will have the skills to obtain focused and structured datasets from the Web that you can then use to augment your own datasets, enrich their dimensions, feed your applications, perform data mining, machine learning, and training, data analysis, AI processing and reasoning and other data management.
