Learn about semantic web standards and knowledge graph application development for free with Ontotext Academy.
Ontotext has offered semantic technology training for nine years. Customers can take classes in which one of our experts trains them in the use of GraphDB, semantic technology, or the assembly of a semantic technology proof of concept. A great new course that follows this model is our Graph RAG Training, where you can learn how knowledge graphs can enhance the use of large language models for more accurate, contextual question answering.
This month we’re announcing a new kind of training called Ontotext Academy, where students can take free, interactive online courses to learn about semantic technology, about building applications with GraphDB, and more. Students who successfully complete a “learning path” — a sequence of courses designed for someone in a particular role — can then download a certificate of completion. They can also have this certificate automatically added to their LinkedIn page.
We feel that these learning paths will help more people understand both the value of semantic technologies and why GraphDB provides an excellent platform for building knowledge graph applications that take advantage of these technologies.
We built these online courses using a Learning Management System (LMS) platform, which tracks each student’s progress using quizzes at the end of each course. Students can re-take any course until they are confident that they know the material and proceed along the learning path at their own pace throughout. When taking an additional learning path that includes courses that the student has successfully completed in a different learning path, there is no need to repeat those courses.
Learning paths and courses
Learning paths are designed around a student’s potential role in an organization:
- The Knowledge Graph Engineer learning path shows a student why graphs can be better than tables for storing data, what makes a graph a knowledge graph, and which standards and tools work together to enable the creation of knowledge graphs that drive successful applications. In addition to learning what each of these standards (for example SPARQL, RDFS, and SHACL) contributes, the student will learn the basics of how to use each of them.
- The Developer learning path also teaches a student about the basic concepts behind knowledge graphs and the relevant standards. It adds a course on how developers can use standard and specialized APIs to bring the power of GraphDB to their own applications.
- The Operations learning path that is currently under development adds a course to the Developer learning path with guidelines about efficient maintenance of a scalable GraphDB cluster, whether it’s being run on local hardware or on one of the popular cloud providers.
The courses that make up these learning paths each take about an afternoon to complete. The following courses are in the Knowledge Graph Engineer learning path, the Developer learning path, or both:
- Introduction to semantic technologies: An overview of graphs, knowledge graphs, RDF standards, triplestores, and how applications get built around these.
- Semantic models with GraphDB: The RDF data model and syntaxes, the assembly and use of schemas and ontologies, the potential role of the Linked Open Data Cloud, and how to use SHACL to ensure data quality.
- SPARQL: Writing SPARQL queries to retrieve, create, and update data using filters, functions, aggregation, property paths, and more.
- APIs, virtualization, and connectors: Using APIs to build knowledge graph applications around the GraphDB triplestore. Also, how to initiate and execute transactions, how to access external relational data, and how to use popular full-text search tools on data stored in GraphDB.
The GraphDB Operations course currently being assembled will cover the efficient installation, configuration, maintenance, and updating of scalable clusters of GraphDB nodes.
Quizzes and certification
Before moving on from one course to the next step of a learning path, the student takes a quiz and must answer 70% of the questions correctly. Some questions require a single answer and some require multiple answers. Some example questions:
Students who successfully pass all of a learning path’s quizzes can download a certificate showing that they have completed the learning path. They can also have that certificate added to the “Licenses & certifications” section of their LinkedIn profile with two clicks:
Assembling these courses has been an interesting experience as we combined text, video, and quizzes to create modules that we could recombine for the different role-based learning paths. We tried to make the courses interactive wherever possible by, for example, providing sample data with the demonstration SPARQL queries so that the reader could execute them to reproduce the results shown in the course.
Another place where the reader can try the course examples themselves is in the “APIs, virtualization, and connectors” course, where sample HTTP API calls are shown with the curl command line utility so that the reader can, for example, add data to or delete it from a GraphDB repository in a locally running copy of GraphDB. (As described in that chapter, in addition to making these calls from the command line with curl, developers can make the same API calls from most modern programming languages. This is what makes it so straightforward for developers to combine their favorite UI frameworks and specialized libraries into an application that uses GraphDB for backend storage, inferencing, and other specialized knowledge graph features.)
The Future of Ontotext Academy
We’ve already mentioned that the Operations learning path is on the way. As we think about other courses and learning paths to add to Ontotext Academy, we’d love to hear your suggestions. Meanwhile, you can go to the Ontotext Academy Welcome Page and follow the link to sign up to learn about semantic web standards and how GraphDB can help you build scalable knowledge graph applications.
Originally published at https://www.ontotext.com on August 2, 2024.
