MSDS 459-DL Knowledge Engineering.

This course reviews knowledge-based systems, intelligent applications, and conversational agents. It uses knowledge graphs to store information about entities and their relationships, where entities represent words, documents, people, organizations, products, places, or other things. Students design graph data models and implement knowledge bases in graph-relational databases. Drawing on these knowledge bases, as well as large-scale language models and inference algorithms, students build recommendation systems and end-to-end applications for information retrieval, information extraction, and question answering. Recommended prior courses: MSDS 431-DL Data Engineering with Go and MSDS 453 Natural Language Processing. Prerequisites: (1) MSDS 420-DL Database Systems or CIS 417 Database Systems Design and Implementation and (2) MSDS 422-DL Practical Machine Learning or CIS 435 Practical Data Science Using Machine Learning.

This course utilizes graph-relational databases with EdgeDB. It also uses the Go programming language. Cross-platform desktop application development is carried out using the Wails programming environment with Go on the backend and with Svelte and Pico on the frontend.

Students benefit by taking the Go Learning Studio and MSDS 431-DL Data Engineering with Go prior to taking this course.

This course is also associated with the Data Engineering specialization.

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