AI and Knowledge Engineering

MSDS 459-DL AI and Knowledge Engineering.

This course reviews knowledge-based systems, intelligent applications, and software agents. It uses knowledge graphs to store information about entities and 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 knowledge bases, large language models, retrieval-augmented generation, graph neural networks, and inference algorithms, students retrieve information about features and utilize it in predictive models. 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 Go and AI-Assisted Programming 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.