Knowledge Engineering

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.

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

This course utilizes graph-relational databases.

This course is aligned with both the Data Engineering and Artificial Intelligence specializations.

Go to the main page for Data Engineering.

Go to the main page for Artificial Intelligence.